[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-4.1] The candidate has extensive experience leading complex, cross-functional technical projects, strong organizational and stakeholder management skills, and a proven ability to deliver end-to-end systems. While not a traditional project manager, their background in engineering leadership, operations, and project delivery demonstrates all core requirements. The only minor gap is the lack of explicit mention of formal project management certifications or methodologies (e.g., PMP, Agile/Scrum), but their track record and fast-learner profile strongly compensate. **✅ Strengths:** - Cross-functional Project Leadership - Technical Systems Architecture - Operational Automation

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5] Strong Python/SQL and automation experience with security and cloud basics; gaps in ETL tools, orchestration (Kubernetes), and enterprise data governance/APIs reduce alignment but are learnable. **⚠️ Critical Gaps:** - Production ETL/ELT tooling (Airflow/dbt) - Container orchestration (Kubernetes) - Enterprise data governance/lineage (e.g., Collibra/Apache Atlas) - GraphQL/SOAP for enterprise integrations **✅ Strengths:** - Python and SQL proficiency for data processing - Containerization (Docker) and cloud basics (AWS) - Security and access control (SSO/RBAC) applied to systems **❌ Missing Required:** ETL/ELT tools experience, Orchestration tools (Kubernetes), GraphQL, SOAP, Data governance/lineage frameworks, Data quality frameworks, Explicit 3+ years enterprise data engineering

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a proven Systems Architect with a strong track record of building complex, automated systems from the ground up. While their Python and general infrastructure skills are impressive, they have significant gaps in the core required stack for this role: Node.js, NoSQL databases, and deep AWS services expertise. **✅ Strengths:** - Deep experience architecting and deploying complete, automated backend systems - Strong foundation in Infrastructure-as-Code (Terraform) and containerization (Docker) - Demonstrated ability to self-teach and master complex technical domains (AI/Cloud) **❌ Missing Required:** Advanced experience with Node.js, Strong experience with AWS services (serverless, compute, storage, IAM, networking), Proficiency with NoSQL databases (MongoDB, DynamoDB, or similar)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong technical foundation with system architecture, automation, and infrastructure experience. The candidate demonstrates problem-solving ability and 'fast learner' potential through self-hosted AI infrastructure and automated e-commerce systems. However, lacks specific corporate ITIL/ServiceNow experience and direct application support background that the role emphasizes. The engineering mindset and Docker/CI-CD experience are valuable, but the role requires more operational support focus than pure architecture. **✅ Strengths:** - System Architecture & Automation: Proven track record building production-grade automated systems (JIT inventory, trading bots) demonstrates strong technical problem-solving - Infrastructure & DevOps Foundation: Docker, Terraform, CI/CD pipelines, Linux, AWS basics align well with infrastructure responsibilities - Business-Technical Bridge: Supply chain and finance background provides excellent context for understanding business requirements and technical translation **❌ Missing Required:** Corporate application support experience, ITIL-based incident classification and management, Ticketing system experience (Jira/ServiceNow/GLPI), Troubleshooting corporate applications

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems architect with Python, SQL, production automation and financial/transactional data experience; lacks explicit data-warehouse and orchestration platform experience but shows high fast-learner potential and transferrable infra skills. **⚠️ Critical Gaps:** - Experience with modern cloud data warehouses (Snowflake/BigQuery/Redshift) - Pipeline orchestration tools (Airflow, Dagster, Prefect) - Dimensional modeling (fact/dimension design for analytics) **✅ Strengths:** - Proven production systems architecting and deployment (metal-up, CI/CD, Docker/Terraform) - Strong Python + analytics experience applied to financial/transactional datasets - Demonstrated ability to design end-to-end automated pipelines and operationalize complex systems **❌ Missing Required:** Deep, demonstrable experience on a data warehouse platform (Snowflake/BigQuery/Redshift), Hands-on pipeline orchestration (Airflow/Dagster/Prefect), Explicit dimensional modeling experience (facts/dimensions)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong match, demonstrating deep, hands-on experience in building and deploying the exact type of automated, AI-driven systems described in the job. His career trajectory shows a clear progression into AI and systems architecture, and he has production-level experience with Python, SQL, and data pipelines. The only minor gap is a specific orchestration tool, which is mitigated by his extensive automation experience. **✅ Strengths:** - Proven experience building production-level automated systems from scratch - Deep practical knowledge of Python and SQL for data-driven logic - Hands-on experience self-hosting and optimizing AI/LLM models **❌ Missing Required:** Airflow (or similar orchestrator explicitly mentioned)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong domain fit in procurement and supply‑chain analytics plus systems/integration and automation skills indicate high ramp potential, but the role requires immediate, hands-on Coupa + SAP S/4HANA Source-to-Pay expertise and a required Coupa certification which are absent. **⚠️ Critical Gaps:** - Coupa (hands-on + certified) — BLOCKING - SAP S/4HANA Source-to-Pay functional/configuration experience — BLOCKING - Coupa–SAP integration & WRICEF experience — BLOCKING - Formal Coupa certification (explicitly required by JD) — BLOCKING **✅ Strengths:** - Deep supply-chain and procurement domain expertise - Systems architect / integrator mindset with track record building production automation - Strong technical toolset for integration and automation (Python, SQL, CI/CD, infra) **❌ Missing Required:** Coupa hands-on configuration experience, Coupa certification, SAP S/4HANA Source-to-Pay functional/configuration experience, Experience authoring WRICEF functional specifications, Demonstrable enterprise-scale procurement transformation (5+ years)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Strong match. The candidate demonstrates core applied experience in predictive modeling and anomaly detection through his work as a Quantitative Developer building risk-management algorithms for trading bots. His extensive history with complex, messy data in finance (algorithmic trading) and logistics (JIT inventory systems) aligns perfectly with the job's primary challenge. While his most direct ML experience is not from the last 3 years, his recent work in AI infrastructure and proven ability to self-teach complex domains mitigates the risk. **✅ Strengths:** - Hands-on experience with messy, high-volume financial and operational data - Proven ability to build automated, data-driven systems (JIT inventory, trading bots) - Strong foundational Python skills for data analysis (Pandas, NumPy) **❌ Missing Required:** scikit-learn (has PyTorch/Pandas, easily transferable)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled systems architect with a strong background in supply chain analytics and process automation. However, he has a critical gap in the required Transportation Management (TM) domain and lacks experience with specific TM solutions, making him a poor fit for this specialized Business Analyst role. **⚠️ Critical Gaps:** - Transportation Management (TM) domain expertise **✅ Strengths:** - Strong technical and systems architecture skills - Proven fast learner with a formal background in supply chain analytics (MIT MicroMasters) - Deep experience in process automation and building production systems **❌ Missing Required:** Familiarity with major TM solutions, Direct experience in Transportation Management processes (planning, execution, carrier management)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate is a highly capable Systems Architect and AI Engineer with outstanding foundational skills in Python, infrastructure (Terraform, Docker), and automation (CI/CD). However, this is a senior Data Engineering role requiring deep expertise in a specific data stack (Spark, Airflow, Kafka, etc.) which the candidate does not possess. While he is a proven fast learner, the significant gap in required tooling makes him a weak match for this specific senior-level position. **✅ Strengths:** - Exceptional Python and systems automation background - Strong Infrastructure as Code (Terraform, CI/CD) and container (Docker) experience - Proven fast learner with a clear trajectory towards complex technical roles **❌ Missing Required:** Trino, AWS Glue, Apache Airflow, Kafka, Spark on Kubernetes, Pyspark, Databricks, Redshift

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong systems thinking, deep Python expertise, and hands-on experience with AI infrastructure, automation, and algorithmic optimization. They have built and optimized self-hosted LLMs, designed feedback-driven systems, and have a proven record of cross-stack engineering. The main gaps are in explicit experience with RLHF, JAX/TensorFlow, and large-scale industry research, but their fast learning and demonstrated ability to master new technologies suggest high adaptability. **✅ Strengths:** - Python & PyTorch expertise - Systems architecture and optimization - Rapid self-learning and adaptation **❌ Missing Required:** JAX, TensorFlow, RLHF

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong alignment on system architecture, Python-based development, data/ML pipelines and DevOps (Docker, Terraform, CI/CD, Git) and meets education and English requirements; minor gaps are primarily in explicit application security tooling and some enterprise-scale cloud/security processes. Candidate's background as an architect and founder suggests high fast-learning potential and ability to fill remaining gaps quickly. **✅ Strengths:** - System architecture and end-to-end infrastructure (incl. local AI clusters) - Python + data/ML engineering (Pandas, PyTorch) and analytics background - DevOps/tooling experience (Docker, Terraform, CI/CD, Linux, Git)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong infrastructure automation, Python/Bash scripting, Terraform, and security experience, with a proven record of building and operating production systems. While AWS and local clusters are highlighted, direct GCP and observability stack (Grafana/Prometheus/Datadog) experience are not explicit, but the candidate's fast-learning profile and deep hands-on skills suggest quick adaptability. Minor gaps exist in specific cloud provider (GCP), observability tooling, and explicit on-call/incident response, but overall alignment is high for a senior infrastructure role. **✅ Strengths:** - Infrastructure Automation (Terraform, Docker, CI/CD) - Python/Bash Scripting - Security & Access Controls (SSO, RBAC) **❌ Missing Required:** GCP, Grafana/Prometheus/Datadog (observability stack)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture and hands-on AI/LLM experience (local clusters, PyTorch, infra, automation) plus solid backend skills (Python, APIs, CI/CD) indicate a fast learner who can map to cloud-managed workflows quickly; however the resume lacks explicit GCP production experience and documented work building/orchestrating AI Agents at scale, which are core requirements. **⚠️ Critical Gaps:** - GCP (Cloud Functions, Cloud Run, managed services) — required and not evidenced - Practical production experience building/orchestrating AI Agents (cloud-integrated) **✅ Strengths:** - End-to-end systems architecture and production deployments (metal-up, JIT systems) - Practical LLM/AI experimentation and local cluster optimization (privacy-focused) - Strong backend engineering with Python and automation for scalable workflows **❌ Missing Required:** GCP platform experience (Cloud Functions/Cloud Run/APIs/managed services), Demonstrated production AI Agents integration/orchestration, Explicit experience with event-driven cloud services (e.g., Pub/Sub) on GCP

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong operational and project delivery background with clear client-facing consulting, procurement/ERP experience and team leadership; lacks explicit experience with common field-work coordination and commercial PM/CRM tooling but shows fast-learning ability and technical maturity. **✅ Strengths:** - End-to-end project delivery and operationalization (founder / engineered JIT system) - Strong automation and technical troubleshooting (Python, scripting, infra) - Finance/procurement background supporting project cost awareness

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong match, possessing direct, hands-on experience with all mandatory requirements: Docker, CI/CD, and Terraform. Their background in building complex, automated systems from the ground up, including self-hosted AI clusters, indicates deep infrastructural knowledge that exceeds the job's requirements. The proven fast-learning ability and startup experience are significant bonuses. **✅ Strengths:** - Direct experience with entire required stack (Docker, Terraform, CI/CD) - Proven ability to architect and build automated, production-grade systems - Deep infrastructure knowledge demonstrated through self-hosting AI clusters

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong match, demonstrating a rare combination of deep, hands-on infrastructure experience (self-hosting LLMs) and a product-oriented mindset from founding an automated business. His career trajectory from finance to AI systems architecture is ideal for a role requiring both technical depth and business acumen. While he lacks experience with specific listed AI tools and formal evaluation frameworks, his proven ability to self-teach and deliver complex production systems mitigates these gaps. **✅ Strengths:** - Proven ability to architect and build entire automated systems from scratch (JIT system). - Direct hands-on experience with AI infrastructure by self-hosting and optimizing LLMs. - Strong product and business acumen demonstrated by founding a company and holding product-adjacent roles. **❌ Missing Required:** Experience designing/running application-level evaluations and integrating them with A/B testing

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong philosophical match, demonstrating exceptional skill in building automated, self-sustaining systems, which is the core of a Platform Engineer role. However, they have a significant gap in the required deep AWS expertise, specifically with services like ECS. Their proven ability as a fast learner and strong background in IaC (Terraform) and CI/CD suggest they could close this gap quickly. **✅ Strengths:** - End-to-end system automation - IaC (Terraform) and CI/CD - Proven fast learner with strong problem-solving skills **❌ Missing Required:** Deep AWS expertise (resume lists 'AWS Basics'), AWS ECS

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is an exceptionally strong systems architect with proven expertise in foundational requirements like Terraform, AWS, Docker, and CI/CD. However, the role is explicitly for a senior Ruby on Rails developer, and the candidate possesses zero experience in this language, which constitutes a critical gap. While he is a fast learner with adjacent skills in Python, the 5+ year RoR requirement is not met. **⚠️ Critical Gaps:** - The core requirement of 5+ years experience in Ruby on Rails is entirely missing. **✅ Strengths:** - Deep, hands-on experience with Terraform for IaC - Proven ability to architect complex, automated systems from scratch - Strong understanding of CI/CD, Docker, and adjacent cloud technologies **❌ Missing Required:** Ruby on Rails, Sidekiq / Resque, RSpec / Minitest, GraphQL

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong match due to direct, hands-on experience in self-hosting LLMs and architecting autonomous systems that function as agents (e.g., JIT inventory system, trading bots). Their career trajectory shows a deliberate and successful progression into the AI/Systems domain, and their strong Python skills are proven across multiple complex, end-to-end projects. **✅ Strengths:** - Direct hands-on experience with LLMs and autonomous agents - Strong, demonstrated Python skills in production systems - Clear career progression towards AI and systems architecture

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] This is a poor fit. The role is for a Senior Frontend Engineer, but the candidate's entire resume is focused on backend systems, AI infrastructure, and systems architecture. There is a critical gap, with no demonstrated experience in JavaScript frameworks, user interface development, or responsive design. **⚠️ Critical Gaps:** - Frontend Engineering experience (the core of the role) vs. candidate's Backend/Infrastructure background. **✅ Strengths:** - Proven ability to learn complex technical domains quickly - Experience with Git and collaborative development - Deep understanding of AI systems from an infrastructure perspective **❌ Missing Required:** Expertise in frontend development, Proficiency in modern JavaScript frameworks (e.g., React, Vue.js, or Angular), Experience developing user-facing components and interfaces

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is disqualified as the position is exclusively for individuals with disabilities (PCD), and the candidate profile does not meet this primary, legally-mandated requirement. Additionally, there is a fundamental mismatch in skills and career level, with the role requiring manual production labor and the candidate being a senior AI and systems architect. **⚠️ Critical Gaps:** - The role is for manual/operational production work, while the candidate's expertise is in high-level AI/Systems Architecture. - The position is exclusively for people with disabilities (PCD), which is a hard filter. **❌ Missing Required:** Pessoa com Deficiência (PCD) status

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] O candidato demonstra forte experiência em backend, automação, infraestrutura, Python, SQL, Git, e metodologias ágeis, além de perfil de rápido aprendizado e entrega de sistemas complexos. No entanto, faltam evidências de experiência prática com front-end moderno (Angular, Vue.js, HTML, CSS, TypeScript/JavaScript) e APIs GraphQL, que são requisitos centrais da vaga. O perfil técnico é robusto e adaptável, mas há lacunas críticas em frameworks e stacks web exigidos. **⚠️ Critical Gaps:** - Angular - Vue.js - TypeScript - HTML - CSS **✅ Strengths:** - Automação e backend robusto (Python, SQL, Docker, CI/CD) - Experiência em integração de sistemas e APIs - Gestão de projetos e entrega de soluções complexas **❌ Missing Required:** Domínio em Angular, Domínio em HTML/CSS, Domínio em TypeScript, Experiência comprovada com Vue.js

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong analytical, automation, and Excel skills, but lacks direct experience with payroll processing, HR routines, and the specific domain of folha de pagamento. While advanced with data, systems, and finance, there is no evidence of hands-on payroll operations or HR document handling. The candidate's technical and process skills suggest fast learning potential, but critical domain gaps remain. **⚠️ Critical Gaps:** - Experiência prática em folha de pagamento - Rotinas de RH e legislação trabalhista **✅ Strengths:** - Excel avançado e automação - Gestão de processos e análise de dados - Raciocínio lógico e experiência em ambientes regulados **❌ Missing Required:** Experiência comprovada em folha de pagamento, Formação em Administração, RH ou Ciências Contábeis

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly accomplished technologist and systems architect with a strong background in engineering, finance, and AI infrastructure. However, this role is a senior specialist position within corporate Human Resources focused entirely on compensation strategy, personnel budgeting, and HR policy. There is a fundamental and critical mismatch of domain expertise and career trajectory, making the candidate a poor fit for this specific opportunity. **⚠️ Critical Gaps:** - The role is in corporate Human Resources (Compensation Strategy), while the candidate's entire experience is in Technology, Engineering, and quantitative finance. **✅ Strengths:** - Strong quantitative and analytical skills - Proven ability to build complex systems from scratch - Strategic thinking demonstrated in finance and logistics **❌ Missing Required:** Experience as a technical reference for compensation systems, Leadership of personnel budget cycles, Designing and implementing variable compensation programs, Experience with corporate HR policies and legal compliance, Consulting with leadership on organizational structure decisions

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate is a strong systems architect with deep experience in Python, automation, cloud basics, and infrastructure, but lacks direct commercial experience with C#/.NET and modern JavaScript frameworks, which are strictly required for this role. Many supporting skills (SQL, cloud, Docker, CI/CD, authentication, clean architecture, Agile, English fluency) are present or easily inferred, and the candidate's fast-learning, system-building background is a major asset. However, the absence of hands-on .NET/C# and frontend JavaScript/TypeScript experience is a significant gap for a full-stack engineering position. **⚠️ Critical Gaps:** - .NET - C# - JavaScript/TypeScript frontend framework **✅ Strengths:** - Cloud and infrastructure automation - System architecture and clean code practices - Rapid learning and cross-domain integration **❌ Missing Required:** 4+ years commercial experience with C# and .NET, JavaScript/TypeScript with a modern framework (Angular, React.js, or Vue.js), Unit testing with NUnit or xUnit, Solid experience with SQL Server

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate is a highly experienced systems architect and engineer with strong technical breadth, but lacks direct, explicit experience in manual QA testing, bug tracking tools, and formal QA processes. While the candidate demonstrates a fast learning curve, deep SDLC understanding, and strong communication, there is no clear evidence of hands-on manual testing or QA tool usage. The candidate's strengths in automation, SDLC, and documentation are relevant, but the absence of QA-specific experience is a notable gap for this role. **⚠️ Critical Gaps:** - Direct manual QA/testing experience - Hands-on use of bug tracking/test management tools **✅ Strengths:** - Deep SDLC and systems architecture knowledge - Strong Python and automation background - Excellent documentation and cross-functional communication **❌ Missing Required:** Previous experience in Quality Assurance with a strong focus on manual testing, Familiarity with bug tracking and test management tools

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] Candidate is fundamentally a backend/infrastructure architect, while the role is for a senior frontend developer. There is zero overlap in core technologies (React, TypeScript). Furthermore, the candidate does not meet the mandatory language (Spanish) and timezone (GMT+2) requirements, leading to disqualification. **⚠️ Critical Gaps:** - The role is for a Frontend Developer, but the candidate's experience is exclusively in Backend, Infrastructure, and Data. - Required language proficiency in Spanish is missing. - Required timezone alignment (GMT+2) is not met. **✅ Strengths:** - Strong backend and infrastructure architecture skills - Proven rapid learning ability in complex domains (AI, trading) - Deep experience in system automation and integration **❌ Missing Required:** React (5+ years), TypeScript, Fluent Spanish level, Comfortable working in GMT+2 timezone

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and AI infrastructure specialist with deep experience in Python, automation, and CI/CD. However, this is a poor fit for a Test Automation role due to a critical gap in frontend development and a complete lack of demonstrated experience with required testing frameworks like Selenium, Playwright, or Pytest. While he shows immense aptitude for learning, the role requires existing, hands-on testing skills he does not possess. **⚠️ Critical Gaps:** - Frontend development experience - Direct experience with test automation frameworks (Selenium, Playwright, etc.) **✅ Strengths:** - Deep Python & backend automation expertise - CI/CD and Docker proficiency - Exceptional, hands-on AI/LLM infrastructure experience **❌ Missing Required:** Hands on experience with test automation for web and APIs, Practical knowledge of automation tools like Selenium, Playwright, Cypress, Experience with testing frameworks, for example Jest, Mocha, pytest, JUnit, Knowledge of test driven development and modern QA engineering practices

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-5-mini] Strong systems architecture and infra experience with proven delivery and fast-learning history, but lacks the role’s two strict requirements: senior Node.js experience and video/HLS domain knowledge, which are blocking for this position. **⚠️ Critical Gaps:** - Senior Node.js development (7+ years) - Video streaming / HLS expertise **✅ Strengths:** - Systems architecture and end-to-end production deployments - Infrastructure automation and containerized ops (Docker, Terraform, CI/CD) - Proven autonomy and fast learning (built self-hosted AI clusters and JIT inventory systems) **❌ Missing Required:** 7+ years of Node development, Experience in Video and HLS

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect with expertise in Python, AI infrastructure, and automation, but has a critical and complete gap in the required .NET/C# and Angular technologies. While possessing adjacent skills like SQL and CI/CD, the core responsibilities of a .NET Developer are entirely outside their demonstrated experience. **⚠️ Critical Gaps:** - The role requires a .NET/C# developer, while the candidate's entire development experience is in the Python and Systems/AI Infrastructure domain. **✅ Strengths:** - Extensive experience with CI/CD pipelines and Git - Proven ability to architect and build complex automated systems from the ground up - Strong understanding of SQL principles, albeit with different database flavors **❌ Missing Required:** .NET, .NET Core, C#, ASP.NET, Angular

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate is a highly capable Systems Architect with demonstrated excellence in building automated, production-grade systems and a strong grasp of relevant infrastructure (AWS, Docker, CI/CD). However, the role's primary requirement is 5+ years of Golang experience, which represents a critical skill gap. The high score reflects exceptional inferred skills and a strong fast-learner track record, suggesting potential but not immediate suitability. **⚠️ Critical Gaps:** - The role is for a Golang Senior Developer, and the candidate has no Golang experience listed. **✅ Strengths:** - Proven experience building automated, production-grade systems from scratch (JIT inventory system). - Strong background in systems architecture and infrastructure (Docker, AWS, CI/CD). - Demonstrated 'Fast Learner' with a track record of mastering new technical domains (AI, algorithmic trading). **❌ Missing Required:** 5+ years of experience in Golang

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate demonstrates exceptional systems thinking, automation skills, and a strong career trajectory towards complex engineering. However, there is a critical gap in the core programming languages required (Java/C++ vs. candidate's Python) and a failure to meet a 'MUST' have requirement for the 'Golden Signal' framework, making them a poor fit for this specific role's hard requirements. **⚠️ Critical Gaps:** - The role requires very strong Java or C++ experience, and the candidate's background is exclusively in Python. **✅ Strengths:** - Proven ability to architect, build, and deploy automated, resilient systems from scratch (JIT Inventory). - Deep expertise in Python for automation, data analysis, and systems logic. - Strong, intentional career progression from business domains to hands-on AI and infrastructure engineering. **❌ Missing Required:** Golden Signal Cyber Reliability (MUST), 6+ years in a dedicated Reliability/Resilience Engineer role, Strong coding experience in JAVA or C++

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is a highly technical Systems Architect specializing in AI infrastructure and automation. The role is for a senior Certified Accountant. There is a fundamental and complete mismatch in professional domains, skills, and career trajectory. The candidate's experience is in engineering and IT, not accounting, BR GAAP, or IFRS. **⚠️ Critical Gaps:** - The candidate is an Engineer/Systems Architect, whereas the job requires a certified professional in Accounting. This represents a completely different career field with no overlap in core responsibilities. **✅ Strengths:** - English Fluency **❌ Missing Required:** Superior completo em Contabilidade com CRC Ativo, Experiência em contabilidade (BR GAAP e IFRS), Conhecimento do sistema SAP

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit. While possessing strong analytical skills and meeting the language requirements, they have zero experience in a contact center or quality analyst role. Their entire career trajectory is in deep technical and engineering domains, which is a complete mismatch for the people- and process-focused responsibilities of this position. **⚠️ Critical Gaps:** - The role requires proven experience as a Quality Analyst in a contact center, but the candidate's background is exclusively in engineering, finance, and AI infrastructure. **✅ Strengths:** - Fluência em Inglês (C2) - Bacharelado completo - Capacidade analítica geral **❌ Missing Required:** Experiência comprovada como Analista de Qualidade em contact center, Familiaridade com ferramentas de monitoramento e avaliação de qualidade

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with a proven track record of building complex, automated systems and a clear career progression towards infrastructure roles. While there is a critical gap in hands-on experience with specific API Gateway management platforms like Apigee or Kong, their foundational skills in CI/CD, Docker, API security, and Python are excellent. Their demonstrated ability as a fast learner suggests they could bridge this gap quickly. **⚠️ Critical Gaps:** - Direct experience setting up, configuring, and managing commercial API/Event Gateway solutions (e.g., Apigee, Kong, Gravitee) **✅ Strengths:** - CI/CD pipeline implementation - Strong foundation in containerization (Docker) and API security (SSO/OIDC) - Proven ability to architect and build complex automated systems from scratch **❌ Missing Required:** API Gateway Management (Apigee, Kong), Experience with observability platforms

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Solid infrastructure + production systems background (Docker, CI/CD, Postgres, systems architecture) and strong fast-learning evidence (10+ years, self-hosted LLMs, end-to-end production builds). Major gaps are the job's explicit back-end language (Java/.NET), messaging platforms, and front-end framework experience which would be needed to hit day-one expectations for a full‑stack/financial-payments team. **⚠️ Critical Gaps:** - Java (Spring Boot) or .NET Core - Kafka or RabbitMQ - Frontend framework (React/Angular/Vue) + JS/TypeScript **✅ Strengths:** - Infrastructure & DevOps: Docker, CI/CD, Linux, Terraform - System architecture and production deployments (high-availability, resilience) - Database and backend automation experience (Postgres, Python, SQL, API integrations) **❌ Missing Required:** Java (Spring Boot) or .NET Core, Kafka or RabbitMQ, Frontend framework (React / Angular / Vue.js), JavaScript / TypeScript, HTML5 / CSS3

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is a highly skilled Backend and Infrastructure Engineer specializing in AI, automation, and systems architecture with Python. The role is for a Senior iOS Mobile Developer requiring Swift. There is a complete mismatch in core technologies, required skills, and career trajectory, making this a poor fit. **⚠️ Critical Gaps:** - iOS Development - Swift Programming Language **✅ Strengths:** - Experience with CI/CD - Proficient with Git - Strong understanding of software development lifecycle **❌ Missing Required:** Swift, ViewCode, MVVM-C, Testes Unitários e de Interface (no contexto iOS), Design System

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] Candidate is a strong systems architect with deep automation, API, and integration experience, but lacks direct hands-on development with Microsoft 365 (Teams, Word, Outlook plugins, SharePoint/OneDrive) and Azure-specific workflows. Many integration, API, and security concepts are present, and DevOps/CI/CD strengths are clear, but the absence of Microsoft ecosystem plugin experience is a critical gap. Fast learning and broad technical foundation suggest high ramp-up potential. **⚠️ Critical Gaps:** - Direct experience building Microsoft Office plugins (Word, Teams, Outlook) - SharePoint/OneDrive integration workflows **✅ Strengths:** - API and automation pipeline development - Security and authentication (OIDC/SAML, RBAC) - CI/CD and DevOps practices **❌ Missing Required:** Hands-on development with Microsoft Teams/Word/Outlook plugins, SharePoint/OneDrive file-sharing workflows

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a strong match due to extensive experience architecting and building complex, automated backend systems in Python. While specific required frameworks (Flask/FastAPI) are not listed, their deep expertise in Python, system design, and proven ability to self-teach complex technologies suggests they can bridge this minor gap very quickly. **✅ Strengths:** - Extensive Python & backend system architecture experience - Proven ability to build and operate entire automated systems from scratch - Strong fast-learner track record with complex technologies **❌ Missing Required:** Flask, FastAPI, SqlAlchemy

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable Systems Architect with strong analytical and automation skills, but they do not meet the core requirements for this role. There is a critical domain gap between their experience in software/AI systems and the job's focus on industrial Project Controls within an EPCM context for the Minerals & Metals sector. While they have some foundational experience in procurement and planning, they lack the required 10+ years in a formal project controls environment and have no experience with industrial plant projects, CAPEX management, or EVM. **⚠️ Critical Gaps:** - The primary gap is the domain: candidate's experience is in software, automation, and finance, while the role requires deep expertise in industrial/chemical EPCM Project Controls. **✅ Strengths:** - Strong background in engineering and systems architecture - Proven ability to learn new, complex domains quickly (AI, Algorithmic Trading) - Experience in procurement, planning, and supply chain analytics **❌ Missing Required:** Minimum 10 years of experience in Project Controls, Solid experience in project management for industrial or chemical projects (especially Nickel), Hands-on experience with revamp/overhaul projects for industrial plants, Knowledge of earned value analysis (EVM)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong automation, scripting, Linux and systems-architecture background with proven production scheduling and pipeline experience, but lacks hands-on experience with the specific enterprise scheduling and ticketing tools (TWS, RMJ, Mainframe, ServiceNow/Jira) required for immediate contribution. **⚠️ Critical Gaps:** - Tivoli Workload Scheduler (TWS) - RunMyJobs (RMJ) - Mainframe connectivity / z/OS (monitoring and adjustments) **✅ Strengths:** - Proven automation architect (built production JIT inventory system) - Strong scripting and systems skills (Python, Shell, Linux, CI/CD) - Systems integration and ops experience (self-hosted AI clusters, automation pipelines) **❌ Missing Required:** Tivoli Workload Scheduler (TWS), RunMyJobs (RMJ), Mainframe connectivity / z/OS operations, ServiceNow, Jira

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is an exceptionally strong technical and analytical architect with deep experience in building scalable systems and data analysis. However, the role is fundamentally a sales-support position within the Large Customer Sales organization, and the candidate possesses no experience in sales, marketing, advertising, or commercial strategy, creating a critical domain gap. **⚠️ Critical Gaps:** - Experience in Sales/Marketing/Advertising domains. The job is in the 'Large Customer Sales' org, but the candidate's background is purely technical, operational, and analytical. **✅ Strengths:** - Deep data analysis and modeling capabilities - Proven ability to architect and build scalable, automated systems from scratch - Strong background in finance and business process optimization **❌ Missing Required:** 8 years of experience in digital media, sales, or marketing roles, Ability to plan, pitch, and execute a start to finish sales strategy

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate has outstanding hands-on technical skills in AI, software development, and infrastructure, which strongly aligns with the project's subject matter. However, there is a critical gap, as his experience is that of a technical architect and founder, not a formal Senior Project Manager in a large enterprise. He lacks the required demonstrated experience in formal governance, agile ceremonies, and client-facing PM documentation. **⚠️ Critical Gaps:** - Lacks experience in a formal Senior Project Manager role focused on governance and process, rather than hands-on technical execution. **✅ Strengths:** - Deep, practical experience in AI infrastructure and software development - Proven ability to architect and build complex, automated systems from scratch - Strong career trajectory towards AI and advanced technology **❌ Missing Required:** Proven project management experience in large companies or consultancies, Mastery of formal agile practices (Scrum, Kanban, Sprint Planning), Experience creating structured PM documents (Project Charter, SOWs, executive reports)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect in the software and AI domain, but the role is for a Project Coordinator in civil construction. There is a fundamental mismatch in domain expertise, with the candidate lacking required experience in construction project management and proficiency in essential AEC software like NavisWorks and Revit. **⚠️ Critical Gaps:** - Experience in Civil Engineering/Construction Project Management - Proficiency with AEC software (NavisWorks) **✅ Strengths:** - Systems architecture - Project management (in IT) - Process automation **❌ Missing Required:** Experiência em coordenação de projetos e acompanhamento de obras hospitalares, hotelaria e/ou edifícios coorporativos, Experiência em compatibilização de projetos utilizando NavisWorks

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong match due to deep, demonstrated experience in Python scripting, Linux environments, and Infrastructure-as-Code (Docker, Terraform), which are core to the role. Their background architecting automated data systems (JIT inventory) and self-hosting AI clusters aligns perfectly with the need to build and scale data ingestion pipelines. The explicit use of GCP is the only minor gap, but it's heavily mitigated by adjacent experience in AWS and strong IaC principles. **✅ Strengths:** - Deep experience in Python and IaC (Terraform, Docker) - Proven ability to architect automated, production-grade systems from scratch - Hands-on experience with self-hosted AI/LLM infrastructure

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Excellent candidate with a strong foundation in Python, systems architecture, and production infrastructure. While specific required frameworks like Django/Chalice and TDD are not explicitly listed, their proven ability to self-teach complex systems (e.g., self-hosted LLMs) and rapid career progression strongly suggest they can learn these quickly. A strong match based on core competencies, demonstrated learning ability, and adjacent skills. **✅ Strengths:** - Deep Python expertise in a systems/data context - Proven ability to architect and deploy production systems from scratch - Strong foundation in modern infrastructure (Docker, CI/CD, AWS) and architecture (Clean Arch) **❌ Missing Required:** Chalice, Django, Django Rest Framework, Testes Unitários, TDD

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] O candidato possui sólida experiência em gerenciamento de projetos complexos, domínio de ferramentas de gestão (MS Office, experiência com automação e integração de sistemas), formação em Engenharia, e perfil pró-ativo. No entanto, faltam experiência direta com projetos SAP, certificação PMP/PRINCE2, e menção explícita a MS Project, Jira ou Trello. As habilidades de liderança e comunicação são inferidas, mas não detalhadas. **⚠️ Critical Gaps:** - SAP **✅ Strengths:** - Gestão de projetos complexos - Automação e integração de sistemas - Formação sólida em Engenharia **❌ Missing Required:** Experiência com projetos SAP, Domínio de MS Project, Jira ou Trello

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] O candidato é um forte candidato devido à sua comprovada experiência na arquitetura e implantação de sistemas de produção complexos, incluindo infraestrutura logística para e-commerce. Sua trajetória de carreira demonstra uma progressão clara em direção a papéis de liderança técnica e sua experiência em gestão de projetos autônomos e gerenciamento de riscos é diretamente aplicável aos requisitos da vaga. **✅ Strengths:** - Experiência comprovada em arquitetura de sistemas logísticos (JIT) e implantação de infraestrutura do zero. - Forte background em gestão de projetos e riscos, demonstrado em múltiplos papéis, incluindo a fundação de um negócio próprio. - Capacidade de traduzir requisitos de negócio em soluções técnicas, alinhado com a necessidade de atuar como ponte entre áreas.

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Candidate clearly meets the imprescindible requirements (programming logic and OOP) and brings strong automation, CI/CD and infrastructure experience; gaps are mainly in specific QA stack (Java/Selenium and explicit test-automation frameworks) and telecom domain knowledge, but the candidate's proven systems-building and fast learning ability make them a good match for upskilling into this role. **✅ Strengths:** - Strong automation and scripting experience (Python, shell, custom pipelines) - Infrastructure and CI/CD knowledge (Docker, Terraform, Linux) enabling test environment setup - System architecture and rapid learning ability—able to pick up new stacks (e.g., Java/Selenium) quickly