[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: Sonnet4] Strong technical foundation with proven AI/ML implementation experience and business acumen, but lacks formal data science background and specific ML frameworks. Fast learner with demonstrated ability to build complex systems from scratch. **Strengths:** - AI infrastructure and LLM deployment experience - Automation and system building expertise - Strong business-technical bridge with proven ability to deliver measurable results **Missing Required:** 5+ years Data Scientist experience, Proven ML/statistical modeling track record, Python data science frameworks

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate is a very strong match, demonstrating extensive technical leadership, architecture design, and automation expertise relevant to the role. Key strengths include complex project coordination, a metrics-driven approach, and a clear career progression into technical leadership and AI infrastructure. While some specific methodologies like OKRs and certain people management frameworks are not explicitly named, the underlying capabilities are strongly inferred or directly demonstrated, showcasing a fast learner with a proactive approach to system development and team management. **Strengths:** - Technical Leadership, System Architecture, & Complex Project Coordination - Automation & AI Expertise (incl. self-hosted LLM clusters) - Metrics-Driven Approach, Continuous Improvement, & Problem Solving **Missing Required:** Asynchronous Practices (technical implementation)

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate is a strong match due to extensive experience in data-driven operations, process automation, KPI definition, and supply chain/e-commerce expertise. Their 'fast learner' profile and career trajectory towards technical and data roles further enhance their suitability, enabling them to quickly adapt to specific tool requirements. **Strengths:** - Data-driven Operations & Process Automation - Supply Chain & E-commerce Expertise - Stakeholder Communication & KPI Management **Missing Required:** Power BI, Amazon QuickSight, Google Data Studio/Analytics, Kibana

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: GPT4.1] The candidate demonstrates strong, recent experience in supply chain, e-commerce automation, and data-driven operations, directly aligning with the job's logistics and analytics focus. Advanced Excel, automation with Python, KPI/reporting design, and stakeholder collaboration are all evidenced, with inferred skills in SQL/data modeling and dashboarding. The only minor gap is lack of explicit mention of Power BI/QuickSight/Kibana, but advanced Excel and rapid self-learning mitigate this. **Strengths:** - Direct supply chain and e-commerce automation experience - Advanced analytics and reporting (Excel, Python, ERP) - Proven fast learner with self-taught technical skills

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: GPT5-mini] Candidate shows strong, recent hands-on analytics and automation experience (Python, data pipelines, ERP reporting) and demonstrable domain experience in finance/quant and operations that map well to the Product Analyst role. The main shortfall is limited explicit experience with Brazil’s payment networks, which is a nice-to-have for this role. **Strengths:** - Proven data-driven problem solving and reporting (ERP cleaning, forecasting, KPI governance) - Strong automation and production delivery skills (Python, automation-first procurement system, CI/CD, Docker) - Relevant finance/quant experience (trading strategy development) and ability to partner with stakeholders

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate demonstrates strong foundational skills in automation, systems architecture, and an 'infrastructure-first' mindset, with a proven ability to deliver complex systems rapidly. However, there is a significant gap in explicit experience with the specific, required DevOps toolset (Azure DevOps, Jenkins, Kubernetes/AKS, Helm, HashiCorp Vault, OpenShift, JFrog Artifactory) crucial for this role, leading to a low match score despite strong transferable skills. **Strengths:** - Strong automation and 'infrastructure-first' mindset - Proven rapid system delivery and problem-solving through project builds - Ability to translate strategic goals into technical execution and manage stakeholders **Missing Required:** Azure DevOps (Repos, Pipelines, Boards, Artifacts), Jenkins (pipelines declarativos e scripted), Azure (infraestrutura, redes, PaaS, AKS), Kubernetes (and AKS), Helm (creation and use of charts), JFrog Artifactory, Azure Artifacts, HashiCorp Vault (policies, integration), OpenShift (deployments, templates, RBAC), Observability tools (specifics like Prometheus, Grafana, Log Analytics - only general concept inferred)

[ANALYSIS_REPORT] **POOR_FIT - While candidate demonstrates exceptional operational excellence, systems architecture capability, and learning agility, this is a technical product management role requiring deep domain expertise in biometrics, authentication, and fraud/identity products that candidate has not developed. The career trajectory (Finance → Supply Chain → Systems Architecture → AI Infrastructure) moves away from product management and toward pure technical operations. Candidate would require significant domain onboarding and product management training. Consider for Operations/Technical Program Management roles instead.** [Copilot: Haiku] Candidate has strong operations and supply chain background with proven ability to build systems and manage complex processes, but lacks core product management experience, biometrics/authentication domain expertise, and the strategic product leadership this role requires. Career trajectory shows technical operations evolution, not product management or fraud/identity domain progression. **Critical Gaps:** - No product management background (role requires 'proven track record in developing and managing globally successful products') - No biometrics, authentication, or document verification domain experience (candidate is operations/supply-chain focused) - No demonstrated experience with fraud & identity products or solutions **Strengths:** - Excellent systems thinking, process optimization, and ability to translate business needs into technical specifications - demonstrated through ERP data cleanup, automation-first procurement system, and ATS job tracking system - Strong communication skills across technical and executive audiences with proven ability to influence stakeholders and adjust unrealistic timelines - Proven ability to master new technical domains independently (TOTVS ERP, trading algorithms, web scraping/ATS) showing intellectual agility and bias to action **Missing Required:** Product management experience at scale, Biometrics/Authentication domain expertise, Global product strategy experience, Fraud & Identity product development background

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: GPT5.1] The candidate has strong experience in operations, process automation, data integrity and stakeholder communication, but the role is a hands-on DevOps/Release Manager position centered on Go development, Git, CI/CD and Linux tooling. There is no explicit or clearly inferable experience with Go, modern CI/CD pipelines, code review tooling, or core DevOps platforms, which creates multiple critical gaps despite some general automation and systems-thinking strengths. **Critical Gaps:** - Experiência comprovada com desenvolvimento em Go (Golang) para atuar como Analista DevOps/Release Manager - Vivência prática com CI/CD e pipelines DevOps em ambiente de engenharia de software - Experiência sólida em code review/auditoria de código e uso de ferramentas de análise estática/qualidade de código **Strengths:** - Forte experiência em operações, supply chain e integridade de dados ERP com foco em previsibilidade e redução de trabalho manual - Capacidade de traduzir necessidades de negócio em regras e lógica operacional detalhada, atuando como ponte entre executivos e equipes técnicas - Histórico de desenho e implementação de sistemas de automação de e-commerce e fluxos de compras/logística com KPIs claros **Missing Required:** Experiência comprovada com desenvolvimento em Go (Golang), Conhecimento avançado de Git (estratégias de branching e comandos avançados), Experiência sólida com CI/CD e pipelines automatizados, Vivência em code review e auditoria de código, Conhecimento de ferramentas de análise estática e qualidade de código (ex.: SonarQube ou similares), Experiência com Linux e shell scripting

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] This candidate presents an exceptionally strong match for the Machine Learning Engineer role, demonstrating extensive practical experience in building and deploying complex, data-driven systems, including self-hosted AI infrastructure. Their career trajectory shows a clear, intentional progression towards technical and AI roles, complemented by a remarkable ability to self-teach and rapidly master advanced concepts. Key required skills like Python, AWS, Docker, MLOps, and foundational Data Science/ML expertise are either directly present or strongly inferable from their impactful projects. **Strengths:** - Demonstrated ability to build and deploy complex automation and AI infrastructure (e.g., self-hosted LLM clusters, automated e-commerce operations). - Proven 'fast learner' with a track record of acquiring advanced technical skills independently, indicating high adaptability and growth potential. - Strong career progression towards technical and AI-focused roles, aligning well with the Machine Learning Engineer/Data Scientist position.

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: GPT5-mini] Strong fit for automation-first system design, CI/CD and cloud (AWS)/Docker, but lacks core required .NET/Azure/SQL skills the role mandates; overall technical approach matches but language/platform gaps are significant. **Strengths:** - Automation-first systems engineering with measurable operational impact (ERP, procurement automation) - DevOps experience: CI/CD, Docker, AWS and pipelines - Rapid delivery and strong systems thinking / fast learner demonstrated by quick end-to-end project delivery **Missing Required:** .NET 8 / C#, AZ-900 Azure Fundamentals, Microsoft and Oracle SQL Databases + PLSQL

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate demonstrates strong transferable skills in automation, scripting, and advanced data analytics, coupled with a proven fast-learner trajectory. However, the role's mandatory requirement for direct experience with the Palantir Foundry platform (including Pipeline Builder, Quiver, and Ontology tool) is entirely unmet, leading to a significant mismatch despite other strengths. **Strengths:** - Strong background in scripting and automation techniques - Demonstrated advanced data analytics capabilities through complex projects - Proven ability to rapidly learn and apply new complex technical domains **Missing Required:** Proven experience with Palantir Foundry development, Strong expertise in Palantir Foundry Pipeline Builder, Experience with Quiver data visualization tools, Proficiency in working with the Ontology tool, Solid understanding of Foundry architecture

[ANALYSIS_REPORT] **WEAK_MATCH** [2.5-Flash] The candidate demonstrates strong foundational technical skills in automation, data management, scripting, and system architecture, alongside relevant domain experience in finance and supply chain. However, a critical gap exists in direct Salesforce platform experience, which is central to this role. While many skills are transferable, the lack of hands-on Salesforce development significantly impacts the match. **Critical Gaps:** - Hands-on experience with Salesforce, especially declarative development (Flows, Validation Rules, Formula Fields, Approval Processes) **Strengths:** - Strong automation and process optimization expertise - Proven ability to build and manage data-driven systems - Fast learner with broad technical and domain knowledge **Missing Required:** Experience working in Agile / Scrum environment

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Haiku] Candidate is a systems architect with strong operations and process automation background, but lacks required .NET/C#, React/Vue frontend, and SQL database expertise. While demonstrating technical capability and fast-learning ability, the skill gap in core required technologies (primary tech stack: .NET Core 6+, React/Vue) represents a critical mismatch. Career trajectory has been finance→supply chain→systems architecture→AI, moving away from full-stack enterprise development. **Critical Gaps:** - No demonstrated .NET/C# experience (primary stack requirement) - No frontend framework experience (React/Vue required) - No enterprise-scale database optimization (SQL Server/PostgreSQL tuning for high concurrency) - No event-driven architecture implementation shown - Career path is operations/automation-focused, not full-stack enterprise development **Strengths:** - Strong systems architecture and process automation background aligns with DevOps culture and automation mindset - Proven ability to deliver complex integrations under time pressure (ATS system in weeks without coding background) - Excellent stakeholder management and business-to-technical translation (C-level interface, specification to engineering teams) **Missing Required:** .NET Core 6+ (required hard skill), React or Vue experience (required hard skill), SQL database experience at enterprise scale with performance tuning, Concurrency and parallelism in managed runtime environments, Clean Code/SOLID/Design Patterns application in enterprise context

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate is a strong match, demonstrating extensive experience in data engineering, automation, and AI infrastructure, including self-hosted LLM clusters and prompt engineering. While direct Azure Data ecosystem experience is not explicit, his 'fast learner' profile and proven ability to build complex production systems suggest rapid adaptability. His career trajectory is intentionally aligned with technical and AI roles. **Strengths:** - Exceptional experience in building and operating 'automation-first' systems and self-hosted AI infrastructure, directly applicable to GenAI and data development. - Strong career trajectory and 'fast learner' profile, demonstrating rapid acquisition and application of complex technical skills in relevant domains. - Proven ability to translate business requirements into technical solutions, manage data quality, and implement DataOps principles. **Missing Required:** Azure Data Ecosystem (Databricks, Data Factory, Fabric)

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate presents a highly relevant background in Supply Chain & Operations, directly aligning with the team's focus and complemented by strong foundational skills in Python, JavaScript, Docker, and CI/CD. While specific framework experience in React/TypeScript and FastAPI is not explicitly stated, the candidate's proven 'fast learner' track record and extensive experience in systems architecture and automation suggest rapid adaptation and robust problem-solving capabilities. **Strengths:** - Exceptional domain expertise in Supply Chain & Operations technology, directly matching team's focus. - Strong backend and infrastructure capabilities including Python, Docker, CI/CD, Cloud, and inferred Kubernetes, API design, and asynchronous programming. - Demonstrated ability as a 'Fast Learner' and 'Automation-First Operator', with a proven track record of building complex systems rapidly. **Missing Required:** React, TypeScript, FastAPI

[ANALYSIS_REPORT] **WEAK_MATCH** [2.5-Flash] The candidate demonstrates strong architectural, automation, and data transformation skills, coupled with a proven ability to learn complex technical domains rapidly. However, there's a notable gap in direct experience with the specific Azure PaaS integration services (e.g., Function Apps, CosmosDB, Azure DevOps) and C# development explicitly required by the role. **Strengths:** - Strong systems architecture and automation mindset. - Proven ability to rapidly learn and implement complex technical solutions. - Exceptional communication and stakeholder management skills. **Missing Required:** C# development, CosmosDB (NoSQL/Graph DB data modeling/partitioning), Hands-on experience with specific Azure PaaS integration services (e.g., Function Apps, Logic Apps, Service Bus, Event Hub/Kafka), Dedicated experience with Azure DevOps for deployments, Explicit unit and scalability testing methodologies, Azure-specific security, authentication, and networking, Azure-specific monitoring tools (Log Analytics, App Insights, Azure Monitor)

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate possesses strong analytical, problem-solving, and systems architecture skills, alongside relevant functional experience in procurement and supply chain which aligns with MM/WM domains. However, a critical lack of direct SAP MM/WM module experience and related technical expertise makes this a poor fit for a role explicitly focused on SAP support. **Critical Gaps:** - Direct SAP MM/WM module experience, which is the core technology focus of the role. **Strengths:** - Strong analytical and problem-solving capabilities - Extensive functional experience in operations, procurement, and supply chain processes - Proven ability to quickly learn new technologies and build complex systems (fast learner) **Missing Required:** 2-3 years relevant SAP experience particularly with MM/WM Modules, Expert knowledge of SAP applications functionality and technology, Configure, present and discuss best practices and functionalities of the SAP WM and MM modules, Knowledge of key SAP application functionality, tables and relationships, Knowledge of SAP customization/extension methodologies, Development skills using SAP toolset, Knowledge of maintenance/patching mechanics and SAP architecture, Solving complex problems across multiple modules (in an SAP context)

[ANALYSIS_REPORT] **WEAK_MATCH** [2.5-Flash] The candidate demonstrates strong capabilities in automation, containerization, and system design, supported by a clear career progression and fast-learner evidence. However, a critical gap exists in explicit Google Cloud Platform expertise, which is a core specialization requirement for this role, alongside missing experience in specific GCP security services and cloud-native networking. **Critical Gaps:** - Expertise in Google Cloud Platform **Strengths:** - Strong automation and system design capabilities, demonstrated through rapid system delivery and operational efficiency. - Proven experience in containerization (Docker) and CI/CD pipeline management, indicative of modern infrastructure practices. - Excellent communication and documentation skills, crucial for team collaboration and process clarity. **Missing Required:** GKE management, Infrastructure as Code tools like Terraform or Cloud Deployment Manager, Cloud security services such as IAM, KMS, and VPC, Cloud cost optimization and FinOps, DNS, load balancing, and networking in the cloud

[ANALYSIS_REPORT] **WEAK_MATCH** [2.5-Flash] The candidate demonstrates strong full-stack and systems architecture experience, proficient in JavaScript, Docker, and CI/CD, and is a proven fast learner. However, there are critical gaps in required backend technologies (Java and Spring) and a hard language requirement (Professional Spanish) is not met, significantly impacting the overall match. **Critical Gaps:** - Java and Spring (backend development) - Professional Spanish (written and verbal) **Strengths:** - Strong full-stack and systems architecture experience with demonstrable impact. - Proficiency in JavaScript, Docker, and CI/CD practices. - Proven fast learner with a strong career trajectory towards technical/AI roles and relevant domain experience. **Missing Required:** React.js, TypeScript, SQL Server, PostgreSQL, Azure (specific services), Kubernetes basics, .NET Development (5+ years, .Net Framework 4.6 / 4.8 or .Net Core 4 / 6)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: GPT5.1] The role requires deep, hands-on ServiceNow platform development (Business Rules, GlideRecord, Flow Designer, Service Portal/AngularJS, complex integrations), which the candidate does not demonstrate. The candidate is strong in process/operations automation, data and supply chain/financial contexts, and shows clear fast-learning capability, but most core ServiceNow-specific skills and years of experience are missing. This makes the profile more of an operations/automation systems architect fit than a direct platform engineer for this stack. **Critical Gaps:** - ServiceNow platform development (Business Rules, GlideRecord, Flow Designer, IntegrationHub, Service Portal widgets) - Front-end development in AngularJS/HTML/CSS for ServiceNow Service Portal - Hands-on experience with complex ServiceNow integrations (Slack, Twilio, Datadog, Azure, etc.) **Strengths:** - Strong automation-first mindset with experience turning messy operations into measurable, streamlined systems - Deep background in supply chain, finance and data-driven decision-making that aligns with financial/receivables context - Proven fast learner with self-taught complex systems (trading algorithms, custom scraping/ATS-style tooling, ERP remediation) **Missing Required:** Demonstrated experience with ServiceNow Business Rules, Script Includes, Client Scripts, UI Actions and GlideRecord, Experience with Flow Designer and IntegrationHub for real automations, Building and maintaining custom Service Portal widgets (HTML, AngularJS, client/server scripts), ServiceNow security model (ACLs, roles, data security), Practical experience with CSM and ITSM modules, Workspace / UI Builder (Polaris), RESTMessageV2 and complex REST integrations within ServiceNow, ServiceNow-specific versioning and governance practices

[ANALYSIS_REPORT] **GOOD_MATCH** [2.5-Flash] The candidate demonstrates robust experience in system architecture, automation-first design, and data-driven solutions, with a proven ability to quickly learn and implement complex technical systems. While specific tools like Terraform, RabbitMQ, and certain programming languages are not explicitly mentioned, the candidate's background and recent projects suggest a high capacity for acquiring these skills. **Strengths:** - Extensive experience in designing, building, and operating complex, automated, data-driven systems with a focus on measurable results and data integrity. - Exceptional ability to rapidly acquire new technical skills (demonstrated via self-taught AI infrastructure and algorithmic trading) and apply "infrastructure-first" thinking to deliver production-ready solutions. - Strong background in systems architecture, operations, and translating strategic intent into concrete engineering scopes, making him adept at bridging technical and business stakeholders. **Missing Required:** Terraform, Packer, Azure, RabbitMQ, Incognito, OAuth 2.0, TypeScript, Node.js, Java, Rust

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Flash] The candidate demonstrates strong systemic thinking, automation expertise, and a fast-learner profile with relevant experience in data integrity and operations architecture. However, there are critical gaps in core technical requirements for this Full Cycle Developer role, specifically lacking extensive hands-on experience with Java Spring Boot, Angular, Kubernetes, and several specific AWS services, as well as foundational languages like TypeScript/Node.js for serverless development. The mismatch in required programming languages and frameworks leads to a very low match score. **Critical Gaps:** - Java 8+ with Spring Boot (3+ years experience, REST APIs) - Angular (frontend framework, components, services, modules, roteamento, RxJS, injeção de dependência) **Strengths:** - Strong system design, architecture, and automation capabilities from an operational perspective. - Proven 'Fast Learner' with a track record of self-teaching complex technical domains. - Solid experience in data integrity, quality, and reporting, especially in ERP environments. **Missing Required:** TypeScript (for serverless APIs), Node.js (for serverless APIs), DynamoDB, Oracle, PL/SQL, Kubernetes (EKS), AWS Cloud Formation (IaC), OAuth 2.0 (Authorization Code, Client Credentials), Explicit Unit Testing (in software development context), Explicit Agile/Scrum methodology experience, AWS SQS, AWS SNS, AWS Step Functions, Explicit AWS Lambda experience, Explicit AWS API Gateway experience

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: Sonnet4.5] This is a critical skills mismatch. The role requires 10+ years of deep SAP FI/CO functional expertise, S/4 Hana implementation experience, and SAP-specific troubleshooting capabilities. The candidate has strong systems thinking, automation, and technical learning ability, but zero demonstrated SAP module experience, ERP implementation background, or financial systems consulting. While the candidate has ERP data cleanup experience with TOTVS, this does not translate to the specialized SAP functional consultant expertise required. **Critical Gaps:** - 10+ years SAP FI/CO functional experience - candidate has TOTVS ERP experience only, completely different platform and skill domain - SAP module troubleshooting and support expertise - no evidence of SAP product knowledge - S/4 Hana implementation and configuration - blocking requirement with zero transferable experience **Strengths:** - Strong systems thinking and automation capabilities - Proven ability to learn complex technical systems rapidly - Fluent Portuguese and English (meets language requirement) - Brazil-based and available for remote work (meets location requirement) **Missing Required:** SAP FI functional expertise (10+ years), SAP CO functional expertise (10+ years), SAP implementation/upgrade project track record, Deep SAP business process knowledge, SAP architecture and patching knowledge, Complex multi-module SAP problem solving

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Sonnet4] Candidate has strong TOTVS ERP experience and systems thinking but lacks the core AdvPL programming requirement. While he's demonstrated ability to learn complex technical skills, this is a specialized development role requiring immediate AdvPL coding capability that cannot be inferred from his background. **Critical Gaps:** - AdvPL development - core requirement for immediate productivity **Strengths:** - Extensive TOTVS ERP experience - Systems architecture thinking - Fast learner with proven track record **Missing Required:** AdvPL programming language, TOTVS Protheus development, Customizations and reports

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Flash] The candidate is a strong match, demonstrating extensive experience in systems architecture, automation, and ensuring data integrity, directly relevant to a Senior Data Quality Engineer role. While specific Big Data, NoSQL, and streaming tools are not explicitly listed, his proven fast learning ability, broad technical background, and strong analytical skills suggest a high capacity to quickly acquire these. His career trajectory shows a clear and intentional progression toward technical and AI infrastructure roles. **Strengths:** - Extensive experience in systems architecture, automation, and data integrity - Proven fast learning ability and adaptability to new technical domains - Strong analytical and problem-solving skills, with excellent communication across stakeholders **Missing Required:** Big Data platforms (Hadoop tools: HDFS, Hive, Spark), Modern streaming technologies (Kafka, Flume, Kinesis), NoSQL databases (Cassandra, MongoDB, HBase), MDM tools, Performance testing applications (JMeter), Data visualization tools (Tableau, Power BI, Tibco Spotfire), Testing frameworks (TDD, DDT, BDT)

[ANALYSIS_REPORT] **GOOD_MATCH** [2.5-Lite] The candidate demonstrates a strong aptitude for engineering and automation, with excellent technical skills and a proven ability to learn quickly, aligning well with the general requirements for an engineering role. However, significant gaps exist in the core automotive-specific services of testing and homologation, as well as specialized automotive domains, which are critical for this role. **Critical Gaps:** - Specific automotive domains (e.g., ADAS & CAV, Body Development, Chassis Development, Durability & Reliability, Electronics, HVAC & thermal comfort, NVH, Passive Safety, Powertrain) **Strengths:** - Engineering Services / Systems Architecture & Automation - Technical Skills (Python, CI/CD, AI/IA, Cloud) - Fast Learner & Proactive **Missing Required:** Testing Services, Homologation Services

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: GPT4.1] The candidate demonstrates strong end-to-end product/system building, data-driven operations, and technical leadership, aligning well with the product/growth mindset and business impact focus. However, there is no explicit evidence of hands-on experience with React.js, Node.js, or TypeScript, though system automation and scripting are present. SQL/NoSQL, API, and cloud concepts are inferred, but lack of direct modern fullstack stack experience is a notable gap. **Strengths:** - End-to-end product/system delivery - Data-driven operations and metrics focus - Proven fast learner and self-starter **Missing Required:** Direct experience with React.js, Node.js, TypeScript

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Lite] The candidate presents a very strong profile with extensive experience in automation and system building, directly applicable to a QA Automation Engineer role. Strengths include programming languages (JavaScript, Python), essential tools (Postman, Git, CI/CD), and inferred QA methodologies. The primary areas for development are explicit experience in performance testing and familiarity with specific tools like Playwright/Selenium. **Strengths:** - Proficiency in JavaScript and Postman - Extensive automation and systems building experience - Advanced English proficiency and Engineering degree **Missing Required:** 5+ years of experience specifically as a QA Automation Engineer (candidate has 6 years of related automation/systems building experience), Familiarity with performance testing tools like JMeter or LoadRunner

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: GPT5-mini] Strong analytical and systems/operations background with demonstrated work on forecasting, ERP data integrity, automation-first inventory/procurement systems and algorithmic trading (modeling/backtests). Missing explicit experience in fraud or credit-risk prevention reduces domain fit for this role but English fluency and client/stakeholder communication are excellent matches. **Strengths:** - Analytical modeling and measurable results (forecasting, trading strategies, backtests) - Systems architecture for operations: automation-first inventory/procurement and ERP data integrity - Fluent English and proven ability to translate technical solutions to executives/stakeholders **Missing Required:** Experience in prevention of fraud or credit risk

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Lite] The candidate demonstrates a strong alignment with the Machine Learning Engineer role, possessing extensive experience in automation, systems architecture, and AI infrastructure. Key required skills like Python, data quality systems, and data pipelines are well-represented, with strong inferences for ML frameworks and deployment practices. The candidate also shows significant potential in preferred areas like GenAI orchestration due to their self-taught AI infrastructure background. Combined with excellent communication skills, a fast learner profile, and a relevant career trajectory, this makes for a very strong match. **Strengths:** - Strong background in automation, systems architecture, and AI infrastructure - Proficiency in Python and experience with data quality/validation systems - Excellent problem-solving, communication, and rapid learning capabilities

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Lite] The candidate presents an exceptionally strong profile with a relevant engineering background, extensive experience in systems architecture, automation, and complex problem-solving, complemented by excellent communication skills and a proven fast-learning ability. Their recent experience and self-taught initiatives closely align with the technical demands of the role. While specific domain knowledge and certain technical certifications are yet to be acquired, their overall aptitude and career trajectory strongly suggest they can rapidly master these areas. **Strengths:** - Systems Architecture & Automation - Complex Problem Solving & Technical Support - Fast Learner & Technical Aptitude **Missing Required:** Autocad, Exact Engineering Degree (Mechanical, Electrical, or Electronic), Specific equipment technical certifications

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: GPT5-mini] Candidate shows strong systems, supply-chain and operations experience, proven supplier/process automation, and fast-learning technical delivery which map well to project management and manufacturability concerns. However, there's limited evidence of explicit DFX/DFM/DFA experience for power-electronics / high-volume hardware NPI and formal manufacturing/process-optimization credentials. **Critical Gaps:** - Power conversion / power-electronics DFX experience (domain-critical for this role) - Demonstrated NPI (New Product Introduction) at scale for hardware **Strengths:** - Supply-chain & procurement systems: built automation-driven purchasing and stabilized lead times - Rapid systems delivery and technical ownership: built production-grade automation and ATS-style systems quickly - Fast learner with technical breadth: self-taught AI infra, trading systems, and full-stack tooling **Missing Required:** DFX/DFM/DFA for power conversion, 7+ years of NPI experience in hardware/power-electronics

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Lite] The candidate demonstrates a strong engineering foundation and systems thinking with significant experience in automation, supply chain management, and process optimization, highly relevant to NPI roles. While direct 'NPI Engineer' title experience may be slightly less than 7 years, the functional capabilities and rapid system delivery suggest a strong fit; a minor gap exists in explicitly stated project management tool proficiency. **Strengths:** - Strong Engineering Foundation & Systems Thinking - Demonstrated Project Management & Process Optimization - Automation & Technical Expertise (incl. Docker, CI/CD) **Missing Required:** Direct 'NPI Engineer' title for 7+ years (candidate possesses strong functional equivalence)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: Sonnet4.5] The candidate demonstrates strong systems thinking, automation experience, and self-taught technical capabilities including Python, AWS, CI/CD, and data quality work (ERP data cleaning, validation logic). However, this is a specialized Data Quality Engineering role requiring 3+ years in that specific domain, plus deep expertise in Big Data platforms (Hadoop, Spark, Kafka), NoSQL databases (Cassandra, MongoDB), ETL tools (Talend, Informatica), and data visualization (Tableau, Power BI) - none of which appear in the candidate's background. While the candidate shows impressive learning ability and transferable skills in automation and data integrity, the critical gap in Big Data engineering experience and specialized tooling creates a significant mismatch. **Critical Gaps:** - No demonstrated Big Data platform experience (Hadoop ecosystem, Spark, streaming technologies) - Missing ETL tooling expertise (Talend, Informatica) - No data visualization tool experience (Tableau, Power BI) - Lacks 3+ years Data Quality Engineering role experience **Strengths:** - Proven data quality work (cleaned 4K+ ERP records, implemented validation controls) - Strong automation-first mindset with production system delivery - AWS and Python experience with rapid technical learning demonstrated **Missing Required:** Professional Data Quality Engineering experience, Big Data platforms (Hadoop, Spark, Kafka), NoSQL databases (Cassandra, MongoDB, HBase), Data visualization tools (Tableau, Power BI), ETL platforms (Talend, Informatica), Testing frameworks (TDD, DDT, BDT), Multi-cloud architecture experience

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Lite] The candidate demonstrates a strong technical foundation with over 10 years of system-building experience and recent, rapid development of a full website and ATS platform using JavaScript and Golang. They meet or exceed requirements for project management, communication (C2 English), and an autonomous, results-driven mindset. While specific modern web frameworks like Next.js and React are not explicitly listed, their proven ability to learn and deliver complex applications rapidly makes them an excellent fit. **Strengths:** - Strong Project Management & Coordination skills for remote teams/agencies. - Autonomous, results-oriented, 'get stuff done' mindset with proven rapid delivery. - Excellent English communication skills and demonstrated ability to build complex web applications.

[ANALYSIS_REPORT] **POOR_FIT** [2.5-Pro] The candidate has a foundational degree in Mechatronics/Robotics, which is adjacent to Mechanical Engineering. However, their entire 10+ year professional career has been in operations, supply chain, and software systems architecture, with no demonstrated experience in the core job requirements of mechanical design, CAD software, or GD&T. This represents a critical domain gap between the candidate's systems/process focus and the role's physical product design focus. **Critical Gaps:** - Mechanical product design experience **Strengths:** - Relevant engineering degree (Mechatronics/Robotics) - Proven fast learner with strong problem-solving skills - Experience bridging business requirements and technical execution **Missing Required:** Strong proficiency with CAD software (SolidWorks, NX, CATIA, or similar), Hands-on experience with GD&T and tolerance stack-up analysis, Knowledge of manufacturing processes (machining, injection molding, casting, etc.)

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Pro] Candidate is an exceptionally strong match, exceeding the core requirements for software development and architecture experience. Their entire career demonstrates the holistic, systems-thinking approach and business-to-technical translation the role requires. Proven fast-learning ability and adjacent experience in AI/ML make them a high-potential fit despite not having a traditional SDE background. **Strengths:** - Holistic systems thinking and process automation - Proven ability to translate business needs into technical solutions - Rapidly learns and applies new, complex technologies (AI, Go, etc.)

[ANALYSIS_REPORT] **STRONG_MATCH** [2.5-Pro] The candidate is an exceptionally strong systems architect with proven leadership as a founder and deep, hands-on experience in the AI/LLM space, including self-hosting infrastructure. While he lacks the specific 7+ years of experience in the required Next.js/React frontend stack, his demonstrated ability to rapidly learn and build a full-stack JavaScript application from scratch, combined with his robust backend and AI skills, makes him a compelling fit for a leadership role. **Critical Gaps:** - Advanced React/Next.js experience **Strengths:** - Deep AI/LLM infrastructure experience (self-hosted clusters) - Proven technical leadership and founder experience ('Head of Engineering') - Demonstrated rapid learning and complex system-building ability (built ATS in weeks) **Missing Required:** Advanced knowledge of React and Next.js, Strong understanding of UI/UX principles

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: Sonnet4] Strong technical foundation with proven systems architecture and automation experience, but missing core data engineering technologies like BigQuery, Spark, and Kafka. Fast learner profile (33yo with self-taught AI/automation track record) mitigates some gaps. **Strengths:** - Python programming - AWS cloud infrastructure - Systems architecture and scalability **Missing Required:** 5+ years data engineering experience, BigQuery/Postgres depth, Spark/Kafka streaming, Airflow/DBT orchestration

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong general systems architecture, automation, data modeling, leadership, and consulting skills, backed by a significant 'Fast Learner' ability. However, there is a critical and complete absence of experience with Salesforce Marketing Cloud and Data Cloud, which are central to this role's requirements for a technical SME. While many skills are transferable, the lack of direct platform expertise is a significant mismatch. **Critical Gaps:** - Salesforce Marketing Cloud and Salesforce Data Cloud specific expertise (SME level) **Strengths:** - Strong systems architecture and end-to-end automation expertise. - Proven leadership, strategic thinking, and ability to bridge business-technical gaps. - Exceptional 'Fast Learner' with a track record of self-taught complex system development. **Missing Required:** Experience in complex Salesforce Marketing Cloud implementations (full cycle), Dominion of Journey Builder, Automation Studio, Email Studio, Mobile Studio, Salesforce-specific data modeling and integrations (APIs, connectors, Data Cloud context)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong systems architecture experience, end-to-end automation, and business-technical translation, aligning well with the job's focus on scalable solutions and product orientation. While direct experience with Node.js, frontend frameworks, and explicit cloud platforms is not shown, the candidate's rapid self-learning, infrastructure projects, and leadership in automation and reporting infer many required skills. The main gaps are specific technology stacks (Node.js, React/Angular/Vue, Docker/Kubernetes), but the candidate's trajectory and adaptability mitigate these. **Strengths:** - Systems architecture and automation - Business-technical bridge and leadership - Proven fast learner with self-taught technical depth **Missing Required:** Direct Node.js backend experience, Frontend framework experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents strong foundational skills in systems architecture, automation, and data pipelines, with relevant experience in quantitative development and financial low-latency systems. They also demonstrate exceptional learning agility. However, the absence of explicit, in-depth Kubernetes, specific cloud platform (AWS/Azure/GCP), IaC (Terraform/Ansible/Pulumi), Go language, and specialized AI serving/vector database experience creates significant gaps for a role requiring 'absolute mastery' in these areas for AI platform architecture. **Critical Gaps:** - Kubernetes (K8s) - Absolute Domain **Strengths:** - Strong systems thinking, automation, and problem-solving skills demonstrated across various domains. - Exceptional learning agility and intentional career progression towards technical/AI roles. - Direct experience with low-latency financial architectures (nice-to-have skill). **Missing Required:** IaC Advanced (Terraform, Ansible, Pulumi), Expertise in Cloud (AWS/Azure/GCP specific managed services like EKS, AKS, GKE, SageMaker, Vertex AI), Go (Golang), Stack AI/Data (Triton Inference Server, TorchServe, Milvus, Pinecone, Weaviate)

[ANALYSIS_REPORT] **POOR_FIT** [Copilot: claude-sonnet-4.5] The candidate demonstrates strong systems architecture and automation thinking, with proven ability to self-teach complex technical domains. However, this role requires hands-on experience with specific data engineering technologies (Spark, AWS Glue, Redshift, Java/DevOps) that are not present in the resume. While the candidate has relevant analytical background and could potentially learn these technologies quickly, the gap between supply chain/business automation and big data engineering pipelines is substantial. **Critical Gaps:** - No demonstrated experience with big data processing frameworks (Spark) - No AWS cloud data services experience (Glue, Redshift) - No data engineering pipeline development at scale **Strengths:** - Advanced English (C2) - meets language requirement perfectly - Strong automation and systems thinking - understands end-to-end pipelines conceptually - Proven fast learner with self-teaching track record (AI infrastructure, trading algorithms) **Missing Required:** Spark (required), AWS Glue (required), Redshift (required), Senior-level data engineering experience

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong expertise in systems architecture, automation, and technical leadership, with direct experience designing robust, scalable systems and leading cross-functional teams. While there is no explicit mention of Java, Angular, or microservices, the candidate's background in architecting automation-first workflows, end-to-end systems, and technical-business translation infers high adaptability and relevant architectural skills. Some nice-to-have skills (UML, Archimate, C/C++) and direct experience with specific tech stacks are missing, but the candidate's fast learner profile and career trajectory toward technical leadership in AI and systems architecture are strong positives. **Strengths:** - Technical leadership and team guidance - Architecting scalable, automated systems - Strategic business-technical alignment **Missing Required:** Java (Microsserviços e aplicações JSF), Angular

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, automation and leadership background with clear production delivery and fast-learning evidence (self-hosted LLMs, trading automation). However, the resume lacks explicit multi-cloud (Azure/AWS/GCP) IaaS/PaaS architecture experience and the stated 4–8 years of cloud-architecture history required by the role. **Strengths:** - Proven leadership and stakeholder communication (executive/C-level interaction, governance cadence) - Hands-on systems architecture and automation (ERP cleanup, automated procurement workflows, end-to-end delivery) - Fast learner with evidence of self-teaching complex infrastructure (self-hosted LLM clusters, trading systems) **Missing Required:** Multi-cloud (Azure/AWS/GCP) architecture experience, Designing IaaS/PaaS enterprise solutions, 4–8 years of cloud-architecture-specific experience, Proven enterprise application platform architecture (explicitly on cloud providers)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate is a strong match due to extensive systems architecture, leadership, and project ownership experience at an enterprise scale. Key strengths include a proven track record in automating complex operations, designing robust systems from scratch, and managing diverse stakeholders. While demonstrating strong infrastructure capabilities, explicit multi-cloud provider architecture experience (Azure, AWS, GCP) is not explicitly detailed, which is the primary area for improvement. **Strengths:** - Extensive Systems Architecture & Infrastructure-first Reasoning - Strong Leadership, Stakeholder Management, and Project Ownership - Proven ability to build and automate complex, enterprise-scale operational systems **Missing Required:** Explicit experience designing solutions on Azure, AWS, and GCP IaaS/PaaS platforms

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents as a highly skilled Systems Architect with robust automation, communication, and business acumen. While lacking explicit demonstrated cloud or AWS transformation experience, their rapid learning capability, direct pursuit of AWS certification, and strong foundational technical skills make them a strong candidate with high potential for the role. **Critical Gaps:** - Required skill: 'evangelising end-to-end technology roadmaps that guide IT transformations toward cloud computing' (missing 'toward cloud computing') - Preferred skill: 'Experience architecting, migrating, transforming or modernizing customer requirements to the cloud' (missing 'to the cloud') **Strengths:** - Exceptional Systems Architecture & Automation Expertise - Strong Communication & C-level Engagement Skills - Proven Fast Learner with demonstrated ability to acquire complex technical skills rapidly (including AWS certification in progress) **Missing Required:** Guidance on IT transformations specifically towards cloud computing

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-4.1] The candidate demonstrates 10+ years in systems engineering, automation, and analytics, with a clear trajectory toward technical architecture and AI infrastructure. Strong experience in business–technical bridging, C-level communication, and end-to-end system delivery aligns well with AWS Solutions Architect requirements. The main gap is direct, large-scale cloud migration/modernization experience, but the candidate's fast learner profile and automation-first mindset mitigate this. **Strengths:** - 10+ years technical and business systems experience - Proven fast learner with self-taught technical depth - Strong business–technical bridge and C-level communication

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5.1] You show strong systems/operations architecture, stakeholder management, and clear evidence of self-taught AI/automation capability, but most of the role’s core requirements are tightly centered on the Azure AI ecosystem and large-scale production AI patterns, which are not present explicitly. Your AI work appears more self-directed and stack-agnostic (self-hosted LLMs, trading bots) than enterprise Azure-focused, and you also lack the mandatory Azure certification and PySpark/large-scale data processing experience. Overall this is a promising but substantially under-aligned profile for a senior Azure AI Solution Architect role. **Strengths:** - Strong business–technical bridge and stakeholder management, including working with executives and defining clear execution logic and KPIs. - Demonstrated ability to self-teach and deliver complex systems quickly (self-hosted LLM infrastructure, trading systems, job scraping/ATS-style tooling). - Solid background in systems and operations architecture for procurement, supply chain, and e-commerce automation, with a clear trajectory toward AI/technical roles. **Missing Required:** 5+ years of hands-on Microsoft Azure experience, Hands-on experience with Azure OpenAI, Hands-on experience with Azure Form Recognizer, Hands-on experience with Azure Cognitive Search, Hands-on experience with vector databases in production AI solutions, In-depth experience fine-tuning and customizing pre-trained AI models, Proven large-scale data processing and AI data engineering on Azure, Strong programming experience with PySpark, Experience architecting AI solutions specifically on Azure (cloud/hybrid/on-prem patterns), Microsoft Certified: Azure Developer Associate (AZ-204)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong profile with 10+ years of relevant experience, a clear career trajectory into AI, and proven hands-on capability with LLMs, ML, and automation. His consulting and leadership roles demonstrate significant solution design and stakeholder management skills. The primary gap is explicit experience with Microsoft Fabric and the Azure ecosystem, which is a required skill for this role. **Strengths:** - Extensive experience (10+ years) in systems, operations, and technical roles, exceeding the requirement. - Proven expertise in AI/ML solutions, including hands-on experience with LLMs and traditional ML, backed by a strong 'fast learner' track record. - Strong solutioning, technical leadership, and client-facing communication skills derived from consulting and founder roles. **Missing Required:** Microsoft Fabric, Azure ecosystem