[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5.1] Strong fit on AI/automation systems, engineering background, consultancy-style work, and LATAM/advanced-English requirements, plus clear trajectory toward AI infrastructure and solution-style roles. However, the profile lacks clear 5+ years of formal technical pre-sales/RFP ownership and specific Microsoft Fabric/Azure experience, which are key expectations for this role. Overall this is a solid match for an AI Solution Architect with delivery and advisory strengths, but somewhat lighter on formal pre-sales credentials. **Strengths:** - Deep automation and systems-thinking background with self-built AI/LLM and trading infrastructures that map well to AI solution design and delivery - Strong business–technical bridge experience across finance, supply chain, and operations, aligning with the advisory and discovery aspects of an AI Solution Architect - Proven fast learner with self-taught advanced domains (AI infra, algorithmic trading) and consulting/freelance history similar to IT services work **Missing Required:** 5+ years experience working in pre-sales, solution consulting, or technical account manager role with a proven track record of leading technical responses to RFPs and RFIs, Clear 8+ years explicitly in IT industry roles (vs mixed operations/finance/IT)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong profile for a Systems Architect role, especially with a focus on automation and AI integration, backed by robust experience in systems design, project leadership, and a proven self-teaching ability in complex technical domains. While some specific security frameworks and cloud architecture experience are not explicitly stated, the candidate's demonstrated capacity for risk management, regulatory translation (business rules), and building scalable systems makes them a good fit. **Strengths:** - Systems Architecture & Automation Experience (10+ years) - AI Integration & Fast Learning (self-taught LLM clusters, algorithmic trading) - Risk Management & Business-Technical Translation (founder, quant roles) **Missing Required:** Cloud architecture (AWS, Azure or GCP), Threat modeling (STRIDE, OWASP)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong background in Systems Architecture, risk management, and automation, coupled with a proven 'Fast Learner' track record, particularly in AI infrastructure. Their extensive experience in the financial sector is a significant advantage for this fintech role. While strong in foundational architecture and risk, the candidate has gaps in specific security frameworks and explicit cloud platform experience, making them a very good, but not perfect, match. **Strengths:** - Extensive Systems Architecture and Risk Management experience (~6+ years). - Proven 'Fast Learner' with self-taught AI infrastructure and strong automation background. - Deep financial sector and business-technical translation expertise, highly relevant for fintech. **Missing Required:** Threat modeling (STRIDE, OWASP), Cloud architecture (AWS, Azure or GCP), DevSecOps practices (security aspects)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: gpt-5.1] You have strong systems-thinking, stakeholder communication, and business–technical translation skills that align with the solution-architecture and documentation aspects of this role, plus a clear fast-learning track record. However, the position is a deeply specialized mobile network / MVNO architecture role requiring hands-on experience with LTE/5G cores, VoLTE/VoWiFi, IMS, telecom signaling protocols, and MVNO environments, none of which appear in your background. As a result, despite good general architecture and communication fit, the lack of telecom network engineering experience makes this a poor technical match. **Critical Gaps:** - No demonstrated experience with mobile network engineering or MVNO architectures (LTE/5G, IMS, VoLTE/VoWiFi, 5G Core). - No exposure to telecom signaling protocols such as MAP, CAMEL, SIGTRAN, DIAMETER, SIP, or OCS/Gy/Sy interfaces. - Career history centered on finance/supply chain operations and general systems/automation rather than telecommunications networking. **Strengths:** - Strong business-oriented communication and ability to engage non-technical stakeholders to define technical requirements. - Proven track record in systems thinking, process automation, and translating messy operations into structured, measurable systems. - Fast learner with demonstrated self-teaching across complex domains (trading systems, automation, ATS-style tooling), supporting potential long-term pivot into new technical areas. **Missing Required:** Excellent understanding of Mobile Networks and its architectures, Experience with MVNO architecture(s) and roaming environments, Solid knowledge of networking principles & protocols in a telecom/mobile context, Experience with network protocols MAP, CAMEL, SIGTRAN, DIAMETER, SIP, Knowledge and experience of OCS and Gy/Sy interfaces, Experience with VoLTE and VoWiFi, Experience with LTE, 5G, IMS, IP technologies and protocols in mobile networks, Experience with 5G Core Mobile Networks, Experience with monitoring tools and protocols in Mobile Networks, Extensive working experience on telecoms, designing and implementing mobile core networks

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate demonstrates strong architectural thinking, system design, and stakeholder management, coupled with a proven ability to learn rapidly and apply new technical skills. However, there are significant critical gaps in direct experience with Microsoft Azure, cloud migration, and Azure Landing Zone design, which are fundamental requirements for this Solution Architect role. The overall years of IT experience also fall short of the stated requirement. **Critical Gaps:** - Microsoft Azure experience (10+ years specifically mentioned for public cloud) - Cloud migration and transformation experience - Azure Landing Zone design and implementation **Strengths:** - Exceptional stakeholder management and clear communication of complex technical information. - Proven ability in systems thinking, operational logic design, and automation-first solutions. - Demonstrated fast-learner with a strong trajectory towards technical and AI infrastructure roles. **Missing Required:** 15+ years of IT experience, Strong troubleshooting skills in Azure & Windows environments, Experience across multiple industry domains (banking, healthcare, insurance)

[ANALYSIS_REPORT] **DISQUALIFIED** [2.5-Flash] The candidate demonstrates strong capabilities in systems architecture, automation, stakeholder management, and a proven fast-learner ability across various domains. However, there are critical gaps in the required deep Microsoft Azure expertise and cloud migration experience, alongside a significant shortfall in the mandated years of IT and public cloud experience, leading to disqualification. **Critical Gaps:** - Microsoft Azure (IaaS/PaaS, Azure Migrate, Azure SQL, Azure Storage, Azure Key Vault, Azure IAM) - Azure Landing Zone design and implementation **Strengths:** - Systems Architecture & Design Expertise - Strong Stakeholder Management & Communication - Proven Fast Learner with Automation Focus **Missing Required:** 15+ years of IT experience, 10+ years in public cloud offerings such as Microsoft Azure, Cloud migration and transformation experience (on-prem to public cloud), Strong troubleshooting skills in Azure & Windows environments

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT5.1] Strong systems thinking, data/process automation, and business–technical bridging align with the architect role, but there is no demonstrated experience with Google Cloud, Salesforce, or modern software/cloud architecture, which are core must-haves for this Senior Solutions Architect position. **Critical Gaps:** - Google Cloud Platform (GCP) proficiency - Salesforce architecture/integration experience - Enterprise-grade cloud/software architecture ownership - Banner platform knowledge (for the education-industry context) **Strengths:** - Business–technical bridge: translating business requirements and financial/operational logic into implementable system rules - Systems thinking and process automation for procurement, inventory, and reporting - Advanced data/analytics mindset (forecasting, risk logic, KPI design) with strong English communication **Missing Required:** Proficiency in cloud technologies, particularly Google Cloud, Proficiency with Salesforce, Demonstrated software architecture and design experience in modern application stacks

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate presents an exceptional match for the role, demonstrating a profound understanding and application of automation, system architecture, and operational excellence principles highly relevant to DevSecOps and FinOps. His strong 'fast learner' track record, direct consulting experience, and strategic communication abilities make him an ideal fit for this customer-facing architect position, effectively mitigating the absence of explicit mentions of certain specific tools. **Strengths:** - Automation & Systems Architecture: Proven track record in designing, building, and operating complex automated systems, translating business needs into technical solutions with a focus on data quality and predictable outcomes. - Customer-Facing & Strategic Communication: Exceptional ability to engage with C-level stakeholders and technical teams, clarify requirements, and communicate complex concepts clearly, honed through independent consulting and leadership roles. - Fast Learner & Adaptability: Demonstrated capacity to rapidly acquire and apply new technical skills, such as self-hosting LLM clusters and algorithmic trading, effectively compensating for specific tool knowledge gaps and enabling quick adoption of new platforms like Harness.

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate presents a strong background in systems architecture, leadership, and operational automation, demonstrating significant 'Fast Learner' capabilities through complex projects and continuous education. However, the role's critical requirement for extensive hands-on experience with Azure PaaS, IIS, .NET, Java, and modern frontend frameworks is largely unmet, constituting major technical domain gaps. **Critical Gaps:** - Extensive Azure PaaS experience (including App Service, Functions, AKS, Container Instances, Landing Zones) - IIS Hosting experience - .NET technology stack - Java technology stack - Angular / React frontend frameworks **Strengths:** - Strong leadership and stakeholder communication skills, functioning as a business-technical bridge. - Proven systems architecture and design capabilities, with an emphasis on operational efficiency and data integrity. - Exceptional 'Fast Learner' with demonstrated ability to self-teach and implement complex technical systems. **Missing Required:** 13+ years of hands-on experience in application development and modernization, Strong web application development experience

[ANALYSIS_REPORT] **DISQUALIFIED** [2.5-Flash] The candidate is automatically disqualified due to failing a hard filter: the job requires a physical presence in Centro do RJ, Brazil, but the candidate is based in São Paulo, Brazil. This geographical mismatch for a fully presential role leads to disqualification.

[ANALYSIS_REPORT] **GOOD_MATCH** [2.5-Flash] The candidate presents a strong profile as a Systems Architect with extensive experience in business acumen, project execution, and stakeholder communication. While there is a significant gap in explicit experience with designing corporate network connectivity architectures (LAN, WLAN, WAN, SD-WAN), his 'fast learner' track record and inferred general networking skills suggest high adaptability. Many soft skills and general architectural responsibilities align well with the role. **Strengths:** - Exceptional communication and business translation skills between technical and C-level stakeholders. - Strong experience in project management, governance, and end-to-end solution delivery. - Proven ability as a 'Fast Learner' with a trajectory towards complex technical roles and continuous education. **Missing Required:** Explicit experience in designing and architecting corporate network connectivity solutions (LAN, WLAN, WAN, SD-WAN)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: GPT5-mini] Strong systems-thinking, automation-first background and demonstrable delivery of data pipelines/automation and reporting; however, key Data DevOps platform skills (Kafka, Docker, AWS) are not documented. Fast learner with 10+ years and cross-functional experience makes this a realistic hire with modest upskilling. **Critical Gaps:** - Apache Kafka - Docker - Amazon Web Services (AWS) **Strengths:** - Automation-first systems design and rapid delivery - Data quality, validation and reporting expertise - Cross-functional communication and stakeholder alignment **Missing Required:** Expertise with data pipeline tools such as Apache Kafka, Proficiency with containerization technologies like Docker, Familiarity/experience with cloud platforms such as AWS, Documented 3+ years in a Data DevOps or clearly equivalent role

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT4.1] The candidate demonstrates strong experience in systems architecture, automation, and business-technical translation, with a proven ability to rapidly learn and deliver complex solutions. However, there is no direct experience with ServiceNow or its certifications, and no explicit evidence of hands-on coding in Angular, Java, JavaScript, Python, or web technologies, which are strictly required for this role. The candidate's strengths in process automation, data integrity, and technical leadership are highly relevant, but the lack of direct platform and coding experience is a significant gap. **Critical Gaps:** - ServiceNow platform experience - ServiceNow certifications - Hands-on coding in required languages (Angular, JavaScript, Java, Python, HTML, CSS) **Strengths:** - Automation and workflow design - Business-technical communication - Data integrity and reporting **Missing Required:** ServiceNow platform experience, ServiceNow certifications, Hands-on coding in Angular, JavaScript, Java, Python, HTML, CSS

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT5.1] Strong systems-thinking, analytics, and automation background but minimal explicit experience with AWS data stack, data warehousing, and modern data engineering tooling, so high fast-learner potential yet clear technology gaps for a senior cloud data engineer role. **Critical Gaps:** - Hands-on AWS data engineering (RDS, Aurora, Glue, Lambda, SDKs) - Production ETL and data pipeline implementation - Modern data warehousing platforms (Redshift, Snowflake) - Infrastructure as Code (CloudFormation, CDK, Terraform) **Strengths:** - Systems-thinking and operations-focused analytics, including cleaning complex ERP data and defining validation/reporting logic - Proven ability to design and implement automation-driven workflows that reduce manual operations and improve data reliability - Strong business–technical translation skills and experience working with stakeholders to turn requirements into executable logic **Missing Required:** ETL experience (designing and running data pipelines), CI/CD pipelines for data or applications, SQL for analytics and data manipulation (explicit), Experience with AWS RDS or Aurora, Experience with AWS Glue, Experience with AWS Lambda in data or application workflows, Use of AWS SDKs for data or application development, Data warehousing experience (Redshift, Snowflake, or similar), Hands-on experience with at least one relational database (Postgres or MySQL) in a data engineering context, Experience with Infrastructure as Code (CloudFormation, CDK, or Terraform)

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: Sonnet4] Strong business process automation background with e-commerce operations experience. Candidate demonstrates systems thinking, automation-first mindset, and has built complex operational workflows. Missing specific AI/LLM integration tools but shows ability to rapidly learn and implement technical solutions. **Strengths:** - E-commerce automation experience - Business process optimization - Systems thinking and implementation **Missing Required:** Zapier/Make/n8n, LLM integration experience

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Sonnet4.5] Candidate demonstrates strong systems thinking, automation expertise, and business-technical bridge capabilities. However, this role requires hands-on software development in Java/Spring Boot, TypeScript/Angular - technologies completely absent from the resume. The candidate's technical profile centers on operations, automation scripting, and business process design rather than professional software engineering. While 'Fast Learner' potential exists (proven by rapid prototyping), the gap from operational tooling to enterprise Java/Angular development is substantial for a Mid-Senior role expecting immediate contribution. **Critical Gaps:** - No Java/Spring Boot backend development experience (REQUIRED) - No TypeScript/Angular frontend development experience (REQUIRED) - No demonstrated professional software engineering background - Role expects Mid-Senior developer contributions - candidate profile is Operations/Systems Architect **Strengths:** - Exceptional business-technical bridge capability - aligns perfectly with evangelizing frameworks to other teams - Proven self-management and autonomous delivery (autogestão requirement) - Demonstrated rapid learning: built complex systems (scraping, scoring engines) without formal programming background **Missing Required:** Java with Spring Boot framework, TypeScript and Angular proficiency, Backend development experience, Frontend development experience, Professional software engineering track record

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT5-mini] Strong systems-architecture, automation and ERP/data-integrity background with proven rapid prototyping and cross-functional leadership, but lacks explicit Salesforce platform experience, Apex development and the required Salesforce certifications which are core to this role. **Critical Gaps:** - Hands-on Salesforce architecture/development (4+ years) — role-blocking - Apex expertise — role-blocking - Required Salesforce certifications (Technical/Application Architect) — typically blocking for architect hire **Strengths:** - Systems architecture and end-to-end automation (inventory/procurement workflows) - Data integrity, ERP (TOTVS) cleanup and robust reporting/KPIs - Rapid prototyping and translating C-level requirements into technical scope **Missing Required:** Minimum 4 years as Salesforce developer/architect, Deep domain knowledge of Sales Cloud, Service Cloud and Marketing Cloud, Apex (demonstrated mastery), Salesforce Certified Technical Architect / Salesforce Certified Application Architect, Java (explicit experience)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Sonnet4] Strong systems thinking and automation experience, but lacks the core technical requirements for a Full-Stack Developer role. Candidate has business operations focus rather than software development background. **Critical Gaps:** - 6+ years full-stack development experience - Frontend frameworks (React/Vue/Nuxt) - Backend development (PHP/Python/Node) - AI design tools experience - Modern web development stack **Strengths:** - Strong systems thinking and automation experience - Proven ability to build complex operational systems - Excellent business-technical bridge skills **Missing Required:** React.js/Vue.js/Nuxt.js, PHP, Python, AI design tools, REST/GraphQL APIs, Database management, Authentication systems, TypeScript, Cloud platforms, Design systems

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT5.1] Strong systems/operations background and proven ability to build complex automation and trading systems, but lacks explicit experience with the core .NET/Angular/TypeScript stack and modern cloud DevOps toolchain requested. **Critical Gaps:** - .NET - C# - ASP.NET Core - Angular - TypeScript - Git - Node.js - REST APIs - PostgreSQL - SQL Server - MongoDB - DocumentDB **Strengths:** - Deep experience designing and stabilizing complex operational and financial workflows with strong data integrity focus - Proven ability to rapidly prototype and ship technical systems (scraping + scoring engine, trading logic, automation utilities) despite non-traditional software background - Advanced English and strong communication with C-level stakeholders, enabling effective business–technical bridging in an international credit context **Missing Required:** .NET, C#, ASP.NET Core, Angular, PostgreSQL, SQL Server, MongoDB, DocumentDB, Git, TypeScript

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate exhibits strong systems architecture, automation, and leadership skills, coupled with impressive self-taught technical capabilities in Python and Linux. However, significant gaps exist in the core development technologies required by the role, specifically .NET, C#, React.js, and Azure, which would necessitate extensive ramp-up. **Critical Gaps:** - .NET Core, C# Development - React.js/TypeScript Frontend Development **Strengths:** - Exceptional systems thinking, automation expertise, and ability to build production systems from scratch, including LLM clusters and trading bots. - Strong leadership and communication skills, adept at bridging technical and business stakeholders. - Proven fast learner with a strong track record of acquiring complex technical skills independently and through continuous education. **Missing Required:** Microservices, Docker, Azure, NoSQL databases

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate demonstrates exceptional alignment with the core responsibilities of mapping, automating, and improving operational processes through engineering solutions. Their rich experience in systems architecture, data integrity, and complex project delivery, combined with strongly inferred Python skills and a proven 'fast learner' trajectory, makes them an outstanding match for this fintech role focused on operational efficiency. **Strengths:** - Comprehensive experience in operational automation and systems architecture, directly addressing core job requirements. - Strong capacity for analytical problem-solving, root cause analysis, and delivering measurable engineering output. - Demonstrated 'fast learner' capability and intentional career progression into technical and fintech domains.

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Sonnet4] Strong mismatch between candidate's operations/automation background and the highly specialized Microsoft Teams technical role. While candidate shows excellent systems thinking and customer-facing experience, lacks the deep Microsoft ecosystem expertise required. **Critical Gaps:** - Microsoft Teams deep technical expertise - Microsoft 365 ecosystem knowledge - Unified Communications architecture - Voice/telephony infrastructure - PowerShell/automation scripting **Strengths:** - 10+ years customer-facing technical experience - Strong systems architecture and operations background - Excellent communication and stakeholder management skills **Missing Required:** 10+ years Microsoft Teams/collaboration platforms experience, Microsoft Teams administration experience, SharePoint/OneDrive/Exchange proficiency, PowerShell scripting skills, Unified Communications engineering background, Teams telephony solutions experience, Microsoft Graph integration knowledge

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Haiku] Candidate demonstrates strong systems thinking, data governance, and automation expertise, but lacks the core technical competencies required for a senior Data Engineer role. Missing hands-on experience with essential tools (Databricks, Spark, Kafka, SQL, Python) and Big Data architectures; these are non-negotiable for the position. **Critical Gaps:** - No demonstrated hands-on Data Engineering experience - No Big Data technology stack exposure (Spark, Databricks, Kafka) - No programming language proficiency (Python/Scala required for role) - Operations/Systems Architecture domain != Data Engineering domain **Strengths:** - Proven ability to design complex systems and workflows (e-commerce automation, ERP data governance) - Strong data quality mindset and implementation of validation/control frameworks - Cross-functional communication between technical and business stakeholders **Missing Required:** Databricks, AWS (no evidence), Data modeling (theoretical only, not applied at enterprise scale), Big Data architecture implementation, ETL/ELT tooling, SQL databases (mentioned but no hands-on proof)

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate presents an exceptional match, demonstrating extensive experience in automation, system architecture, and a strong problem-solving acumen. His "Fast Learner" trajectory and ability to deliver complex systems with inferred coding skills directly align with all required qualifications and most desirable ones, especially in test execution, root cause analysis, and communication. **Strengths:** - Exceptional problem-solving & root cause analysis - Strong automation & systems architecture expertise - Proven ability to rapidly acquire and apply new technical skills

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate presents an exceptional profile, demonstrating over 7 years of experience in systems architecture, automation, and data-driven solutions. Their proven ability to rapidly prototype complex systems, combined with a strong 'fast learner' track record and continuous career progression towards technical and AI roles, makes them a compelling fit for an SDE role at Amazon, particularly one focused on building scalable systems. The depth of experience in designing and implementing end-to-end solutions, despite a non-traditional programming background, aligns perfectly with the problem-solving and architectural expectations of the role. **Strengths:** - Exceptional System Design & Architecture experience - Strong track record of delivering complex, automated, data-driven solutions at scale - Proven 'Fast Learner' with relevant career trajectory and continuous self-improvement **Missing Required:** Object-Oriented modeling (explicit demonstration)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Haiku] While the candidate demonstrates strong systems thinking, architectural reasoning, and proven ability to build production systems, there is a critical domain mismatch: the candidate has no full-stack web development experience (React/Java/Python web stack) and no background in BSS/OSS software products. The candidate's 10+ years are in operations, supply chain, and infrastructure—not frontend development or enterprise software engineering. **Critical Gaps:** - No full-stack web development experience (React + Java/Python) - Career trajectory is Operations/Finance → Architecture, NOT software engineering - No demonstrated frontend development work - No enterprise software product delivery experience **Strengths:** - Exceptional systems thinking and ability to translate business logic into technical execution - Proven track record of building complex production systems (ERP automation, trading systems, ATS platform) - Strong business acumen and ability to operate as technical-business bridge with C-level stakeholders **Missing Required:** 2+ years full-stack developer experience (candidate is 0 years in this role), React experience, Java or Python backend web development, Relational database development experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate demonstrates strong experience in designing and implementing automation-first data systems, data quality, and operational reporting. Their proven 'fast learner' track record and ability to build complex production systems from scratch, coupled with excellent communication skills, make them a good fit. However, the lack of explicit experience with several specific data engineering tools (e.g., Airflow, Spark, Kafka, Snowflake, AWS/GCP) listed in the job description prevents a 'strong match', despite strong inference of underlying capabilities. **Strengths:** - Extensive experience in designing and implementing automation-first data systems, ensuring data integrity, and building reliable operational workflows. - Exceptional self-learner with a proven ability to rapidly acquire complex technical skills (e.g., AI infrastructure, algorithmic trading) and deliver production-grade solutions. - Strong communication and leadership capabilities, effectively bridging technical and business stakeholders and translating strategic intent into concrete engineering scope.

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate is a very strong match for the operational and backend aspects of the Senior Full Stack Developer role, demonstrating extensive experience in systems architecture, end-to-end ownership, and managing production environments with a focus on reliability. Their proven fast-learner track record and career trajectory further enhance their profile. However, there are notable gaps in explicitly demonstrated frontend development expertise and experience with specific compiled/functional languages mentioned as requirements. **Strengths:** - End-to-end System Ownership & Operational Excellence - Robust System Design, Data Modeling, & Algorithmic Problem Solving - Exceptional Learning Agility & Technical Adaptability **Missing Required:** Proven strong experience in building and evolving frontend applications with focus on performance and maintainability., Professional experience with at least two compiled or functional languages (e.g., C/C++, Java, Go, Rust).

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate demonstrates strong transferable skills in automation, systems architecture, and AI infrastructure, along with excellent English communication. However, a significant gap exists in explicit Bash/PowerShell proficiency, which is central to this role, necessitating a balanced evaluation. **Strengths:** - Strong automation and systems architecture experience, indicating aptitude for the role's core tasks. - Proven experience with AI infrastructure and LLMs, directly relevant to the job's AI-focused context. - Excellent communication skills and demonstrated 'fast learner' ability, indicating high adaptability. **Missing Required:** Expert-level proficiency in Bash and/or PowerShell scripting (explicitly named tools), 2–3+ years of hands-on experience in at least one of Bash or PowerShell (explicitly named tools)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4.5] The candidate has strong systems thinking, automation expertise, and proven self-learning capability (built trading algorithms, complex operations systems). However, this is a frontier ML research role requiring deep ML theory, published research, and hands-on model training experience with PyTorch/JAX. The candidate lacks formal ML research credentials, no evidence of training models, and no published work—critical gaps for a research scientist position. **Critical Gaps:** - ML Research Experience - No evidence of training foundational models or deep learning research - Academic ML Publications - No published work at ML conferences - ML Framework Proficiency - No demonstrated PyTorch/JAX experience **Strengths:** - Financial domain expertise with trading algorithm experience—direct relevance to 'foundational models for financial applications' - Proven self-starter with fast learning track record (built trading systems, automation infrastructure, ATS system without formal CS background) - Systems thinking and end-to-end ownership mindset—aligns with 'Ideas to PoC to MVP to production' workflow **Missing Required:** Strong ML research background (theory and practice), Experience with frontier labs or published ML research, Hands-on model training and evaluation

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5.1] Strong match on systems thinking, automation, and end-to-end solution design with clear evidence of self-taught software development (scraping engine, trading algorithms, e-commerce automation), plus excellent language fit and Brazil location. Main gaps are lack of explicitly listed programming languages and standard SWE stack signals (Agile, web services, Linux/DB) that modern ATS keyword filters expect for an SDE role. Overall this profile aligns well with a backend/infrastructure-leaning SDE, but would be penalized somewhat by keyword-driven filters. **Strengths:** - Histórico sólido de arquitetura e automação de sistemas em operações, supply chain e trading, mostrando forte capacidade de design end-to-end. - Evidência clara de autoaprendizado avançado e rápida curva de aprendizagem em domínios técnicos complexos (trading algorítmico, scraping, automação de e-commerce). - Excelente ponte negócio–técnico, com experiência em traduzir requisitos operacionais e financeiros em lógica de sistema, KPIs e controles robustos. **Missing Required:** Proficiência explicitamente declarada em pelo menos uma linguagem de programação da lista (C, C++, C#, Java, Python, Golang, Kotlin, JavaScript, Clojure ou outra OOP), Menção clara a experiência com metodologias Agile/Lean (Scrum, Kanban, etc.), Menção explícita a desenvolvimento em ambiente UNIX/Linux, Menção explícita a uso de banco de dados (SQL/NoSQL) em aplicações, Menção explícita a Web Services / APIs (REST/SOAP)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: gpt-5.1] You have strong domain experience in supply chain, ERP-driven operations, and automation plus clear systems-thinking and fast-learning signals, but the role requires a seasoned backend engineer with explicit experience in event-driven microservices, high-throughput data pipelines, and specific backend stacks. Your resume does not yet demonstrate 5+ years of hands-on backend development with Go/Python/Node/Rust, production microservices, or deep database performance/scalability work, which are core to this position. As written, you would likely be screened out in favor of candidates with clearer backend engineering depth. **Critical Gaps:** - No demonstrated production experience designing and operating event-driven microservices using Kafka/RabbitMQ/BullMQ or similar messaging technologies - Lack of clear 5+ years of hands-on backend software engineering building user-facing products (roles are primarily operations/analytics/consulting with light implied coding) - No explicit track record of designing and scaling high-performance backend systems handling large volumes of real-time industrial or sensor data **Strengths:** - Deep domain expertise in supply chain, procurement, ERP data quality, and operational analytics closely related to industrial operations - Strong systems-thinking and automation-first mindset, with experience designing workflows that reduce manual work and improve data reliability - Clear evidence of fast learning and self-directed upskilling, plus an engineering degree that satisfies the formal education requirement **Missing Required:** 5+ years of backend development experience focused on user-facing products, solid experience building event-driven applications with Kafka, RabbitMQ, BullMQ, or similar, deep understanding and practical use of microservices architecture and distributed system design, proficiency in at least one of Go, Python, Node.js, or Rust for backend services, demonstrated in production, proficiency in both relational and non-relational databases with a focus on performance and scalability (e.g., PostgreSQL, ClickHouse, ScyllaDB, Cassandra, MongoDB), experience building and maintaining data-intensive, high-performance backend services in a high-growth, product-driven environment

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong architectural and leadership skills, excellent communication, and a proven fast-learning ability. However, a critical gap in C# and .NET development, which is a primary requirement, significantly reduces the match. Several other required hard technical skills like automated testing, microservices, and message queues are also missing or not explicitly demonstrated. **Critical Gaps:** - C# - .NET **Strengths:** - Scalable & Resilient Architecture Design - Business-Technical Translation & Communication - Adaptability & Continuous Learning (Fast Learner) **Missing Required:** Automated Tests, TDD, BDD, Microservices, Message Queues, SOLID Principles, Clean Code, Design Patterns (specific), Scrum, Kanban, Segurança da Informação (in-depth), Git

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate presents a strong profile with extensive operational, systems architecture, and leadership experience, demonstrating a proactive mindset, strong communication, and the ability to work with complex systems. They are also a proven fast learner. However, the core requirement for professional experience with PickBASIC or other MultiValue database programming environments is critically missing, leading to a direct mismatch for a 'PickBASIC Developer' role. Experience with modern front-end frameworks (React/JavaScript) and explicit Agile/Scrum experience are also not present. **Critical Gaps:** - PickBASIC or other MultiValue database programming environments **Strengths:** - Strong operational and systems architecture experience, particularly in automating complex workflows and ensuring data integrity. - Exceptional communication and leadership skills, enabling effective collaboration with technical and business stakeholders. - Proven fast learner with a proactive, can-do attitude and extreme ownership, demonstrated by self-teaching complex domains and tackling challenging problems. **Missing Required:** React, JavaScript, or modern front-end frameworks, Experience working on Agile / Scrum teams

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong transferable skills in automation, systems architecture, leadership, and problem-solving, along with a 'fast learner' trajectory. However, the critical absence of any explicit hands-on experience with Microsoft Azure as a platform, including its core services and associated tools (IaC, CLI), makes this a poor fit for a 'Senior Azure Engineer' role. **Critical Gaps:** - Extensive hands-on Microsoft Azure experience (5+ years in production environments) - Expertise in specific Azure services (App Services, Azure Functions, AKS, Azure SQL, Cosmos DB, Storage Accounts, Virtual Networks, Load Balancers, Application Gateway) **Strengths:** - Strong automation and systems architecture experience - Proven technical leadership and communication skills - Fast learner with strong career progression towards technical roles **Missing Required:** Infrastructure as Code (IaC) tools (ARM, Bicep, Terraform), PowerShell, Azure CLI, C#, Azure Cloud Networking, Azure Cloud Security Best Practices

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong match on operations-to-technical bridge, end-to-end automation, ERP/data integrity and production integrations, but lacks any demonstrated ServiceNow platform development experience required for the role. Candidate is a proven fast learner and has many adjacent/inferable skills that reduce but do not eliminate the gap. **Strengths:** - Proven delivery of production automation systems tying demand, procurement and inventory - Deep practical ERP data integrity and supply-chain forecasting experience - Demonstrated rapid self-learning and shipping of complex systems (trading engines, scraping + scoring) **Missing Required:** Direct, demonstrable ServiceNow Developer experience (platform projects or modules), Platform-native implementation experience for Incident/Change/Service Catalog modules

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-5.1] The job description is extremely high-level but asks for 5–8 years of experience and alignment with digital transformation and reinvention, which the candidate exceeds with 10+ years across operations, finance/supply chain, and systems-building. Their track record in automation-first operations, ERP data integrity, and quantitative projects matches well with a transformation-focused consulting/tech environment, and their documented fast-learning history boosts their fit despite the lack of explicit tech stack requirements. **Strengths:** - Strong track record of automation and digital transformation in operations and supply chain contexts - Proven ability to act as a business–technical bridge with executives and engineering teams - Fast-learning, quantitatively strong background aligned with continuous upskilling and reinvention

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate presents a strong background in systems architecture, automation, and data management with a remarkable ability to learn and adapt to new technologies. However, the job requires deep and essential expertise in PowerBuilder and .NET, which are completely absent from the candidate's resume, creating critical gaps that fundamentally impede suitability for the role's core development tasks. **Critical Gaps:** - PowerBuilder - .NET **Strengths:** - Exceptional ability to learn new technologies and complex systems quickly, evidenced by self-taught AI and algorithmic trading. - Extensive experience in systems architecture, automation, and data integrity across diverse operational and financial domains. - Strong leadership and project management skills with a clear focus on business value and systemic problem-solving. **Missing Required:** Sybase SQL Anywhere, Threads (in PowerBuilder or .NET)

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-5-mini] Candidate demonstrates strong systems-architecture, end-to-end automation and quantitative/operational engineering experience and infers many backend/cloud skills, but the job has a hard demographic requirement (PcD) which the candidate does not meet, causing automatic disqualification. Additionally, several platform-specific technologies listed by the role (e.g., Clojure, Kafka, Datomic/DynamoDB, Kubernetes, Prometheus) are not demonstrated explicitly. **Critical Gaps:** - Demographic requirement: role is explicitly for persons with disabilities (PcD) and candidate is not PcD — automatic disqualification **Strengths:** - End-to-end automation & systems architecture for operational domains (procurement/inventory workflows) - Quantitative/algorithmic trading systems with strong risk controls and measurable results - Large-scale data integrity and ERP remediation (proven delivery and business impact) **Missing Required:** Practical, demonstrable backend programming experience with explicit frameworks/languages as requested (no explicit language/frameworks listed in resume), Kubernetes / container orchestration experience (not shown), Cloud deployment experience with AWS CI/CD (not shown explicitly), Kafka or equivalent event-streaming experience (not shown), Infrastructure-as-Code practice (not shown)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate presents a strong technical background in systems architecture and automation, with significant client-facing and communication skills. While demonstrating a high technical match and a strong learning aptitude, the absence of Spanish fluency, a critical language requirement for this LATAM client-facing role, results in disqualification. **Critical Gaps:** - Spanish fluency (required for primary technical point of contact in LATAM) **Strengths:** - Strong systems architecture and automation-first operations experience. - Exceptional communication and client-facing skills demonstrated across various roles. - Proven fast learner with a strong, intentional career trajectory towards technical and AI roles. **Missing Required:** Spanish fluency, Hands-on experience with at least one major cloud provider (explicit), Windows platforms

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] Candidate demonstrates strong systems building, data quality, and automation skills with a clear career progression towards data-heavy roles. While possessing significant transferable skills and a 'fast learner' track record, several key Data Engineering tools and concepts like PySpark, Data Warehousing, Databricks, and CI/CD workflows are explicitly missing from their profile. **Strengths:** - Proven ability to build and automate complex systems - Strong focus on data quality, integrity, and operational logic - Exceptional 'fast learner' with a clear career trajectory into technical/AI roles **Missing Required:** PySpark, Data warehousing concepts, Experience with modern data platforms (e.g., Databricks), Knowledge of data integration techniques (reprocessing, historical backfill, partitioning), CI/CD workflows

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong profile with extensive leadership, systems engineering, and data analysis experience. Their proven "fast learner" aptitude, evidenced by self-taught AI infrastructure and algorithmic trading, directly aligns with the need to stay current in ML/AI. While direct, explicit experience with specific ML frameworks and MLOps practices like CI/CD is not detailed, their transferable domain experience and ability to build scalable systems provide a solid foundation for a Senior Machine Learning & LLM Engineer role. **Strengths:** - Strong leadership and cross-functional collaboration skills, demonstrated across various operational and technical roles. - Exceptional self-taught capability in complex technical areas (AI infrastructure, algorithmic trading), indicating high adaptability and a continuous learning mindset. - Extensive experience in data analysis, system design, and building scalable automation solutions, forming a robust engineering foundation. **Missing Required:** Explicit experience with specific ML frameworks (TensorFlow, PyTorch, scikit-learn), Formal experience with code reviews in a software development context, Experience implementing CI/CD pipelines for ML projects, Explicit experience with feature engineering for ML models, Specific expertise in ensuring security for ML models and AI systems

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4] Strong systems thinking and automation background, but critical gaps in core ML/AI requirements. While candidate shows excellent self-learning ability and technical progression, lacks the 4+ years ML experience and hands-on expertise with Python ML frameworks required for a Senior ML Engineer role. **Critical Gaps:** - 4+ years ML/AI experience - candidate has systems/operations background - Advanced Python ML frameworks expertise - no demonstrated ML model development - NLP and LLM hands-on experience - missing core technical requirements **Strengths:** - Strong systems thinking and automation expertise - Proven self-learning ability with technical progression - Excellent communication and stakeholder management skills **Missing Required:** Machine learning model development, Python ML frameworks, Data preprocessing for ML, Feature engineering, Model optimization, Team leadership in ML context

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4] The candidate demonstrates strong technical architecture and systems thinking skills with proven ability to build complex automated systems, but lacks direct AI/ML engineering experience and most required Python AI libraries. While they show excellent learning ability and relevant technical foundation, this represents a significant career pivot from operations/systems to specialized AI engineering. **Critical Gaps:** - No demonstrated experience with GenAI development - Missing all required AI/ML libraries and frameworks - No hands-on experience with modern AI architectures **Strengths:** - Strong systems thinking and architecture skills - Proven ability to rapidly learn new technologies - Excellent business-technical bridge capabilities **Missing Required:** Python AI libraries (Langchain, FastAPI, LlamaIndex, crewAI, Langgraph), Practical GenAI experience, RAG systems experience, Vector databases, Multiagent system architecture

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a compelling trajectory towards AI, demonstrating strong leadership, communication, and hands-on experience building and operating LLM infrastructure and complex data processing systems. While Python and general ML concepts are strongly inferred, the lack of explicit mention or demonstrated advanced expertise in specific ML frameworks (TensorFlow, PyTorch, scikit-learn) is a critical gap for a Senior ML & LLM Engineer role. **Critical Gaps:** - Advanced expertise in specific ML frameworks (TensorFlow, PyTorch, scikit-learn) **Strengths:** - Proven leadership and communication skills, adept at translating technical concepts to business stakeholders. - Practical, hands-on experience with LLM infrastructure development from scratch. - Strong capabilities in data preprocessing, feature engineering, and applying analytical models for business outcomes.

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate is an exceptionally strong match, demonstrating deep experience in LLM infrastructure, data quality, and technical leadership, with a strong career trajectory towards AI. While specific mentions of formal 'code reviews' and 'CI/CD processes' are absent, their experience in building and operating production systems and LLM clusters implies practical familiarity. The 'Fast Learner' bonus further strengthens their adaptability, making them a highly promising candidate for this Senior Machine Learning & LLM Engineer role. **Strengths:** - Strong LLM/AI Infrastructure development and operational experience. - Proven expertise in data quality, preprocessing, and analytical system design. - Demonstrated technical leadership, cross-functional communication, and business-to-technical translation. **Missing Required:** Code Reviews, CI/CD processes, Advanced expertise in specific ML frameworks (TensorFlow, PyTorch, scikit-learn)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate presents a strong match for the Senior Machine Learning & LLM Engineer role, demonstrating significant inferred and direct experience in LLM technologies, scalable AI systems, and data-driven optimization. While specific experience in code reviews and CI/CD processes is not explicit, the candidate's leadership and rapid development background suggest strong potential for quick adoption. **Strengths:** - Extensive experience in LLM technologies and scalable AI systems, including self-hosting LLM clusters. - Demonstrated leadership in engineering and operations, coupled with effective communication skills for complex concepts. - Strong track record in data preprocessing, feature engineering, and model optimization through various projects. **Missing Required:** Code reviews, CI/CD processes

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4] This is a poor fit. The candidate has strong systems/operations background and automation skills, but completely lacks the core ML/AI technical requirements. No Python programming experience, no ML frameworks, and no demonstrated machine learning project work. **Critical Gaps:** - No Python programming experience - No machine learning framework experience - No demonstrated ML/AI project work **Strengths:** - Strong analytical thinking - Automation and systems experience - Business-technical bridge skills **Missing Required:** 4+ years ML/AI experience, Advanced Python expertise, ML frameworks knowledge, NLP/LLM technologies, Data preprocessing/feature engineering, Model optimization experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong analytical and systems-building background, demonstrating relevant experience in data processing, algorithmic logic, and self-taught AI infrastructure (LLMs). While key gaps exist in explicit mentions of modern ML frameworks, code reviews, and CI/CD processes, their proven leadership, communication skills, and rapid learning ability make them a strong, though not perfect, fit. **Strengths:** - Demonstrated ability to lead technical initiatives and effectively communicate complex concepts. - Strong track record in building and operating data-driven automation systems, including self-taught AI/LLM infrastructure. - Exceptional 'fast learner' with a clear career progression towards technical and AI-focused roles. **Missing Required:** Code reviews, CI/CD processes

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4.5] The candidate shows strong systems thinking, automation expertise, and self-teaching capability, but lacks the core ML/AI engineering experience required. While they've built practical systems (trading algorithms, automation pipelines), there's no evidence of Python ML frameworks, model development, NLP work, or the 4+ years of hands-on ML engineering this senior role demands. The career trajectory shows movement toward technical roles, but they're currently at operational/systems architecture rather than ML engineering. **Critical Gaps:** - No demonstrated ML/AI engineering experience - candidate's background is in operations/systems architecture, not ML model development - Missing 4+ years ML/AI experience requirement (has operations/automation experience instead) - No evidence of Python ML framework usage (TensorFlow, PyTorch, scikit-learn) - No NLP or LLM development experience shown **Strengths:** - Advanced English (C2) meets language requirement - Proven fast learner with self-teaching track record - Strong systems thinking and automation-first approach that could translate to ML pipelines **Missing Required:** 4+ years machine learning/AI experience, Advanced Python with ML frameworks, NLP and LLM technologies, Model optimization and feature engineering, Leading ML technical teams