[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit for this role. There is a fundamental and critical gap between the candidate's modern technology stack (Python, AI Infrastructure, Cloud) and the job's requirements for a legacy Microsoft ecosystem (PowerBuilder, ASP.NET, VB6). The candidate's career trajectory shows a clear and intentional move towards modern systems, which is the opposite direction of this maintenance-focused role. **⚠️ Critical Gaps:** - Candidate's entire domain of expertise (Modern AI/Cloud/Python) is fundamentally different from the job's required domain (Legacy Microsoft Enterprise Stack). **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex domains. - Strong systems architecture and automation background. - Fluent English for technical documentation and communication. **❌ Missing Required:** Sybase PowerBuilder experience, Sybase PowerBuilder certification, ASP.NET and C# .Net, Visual Basic 6.0 and ASP, Mainframe integration using COMTI, IIS and COM/COM+ administration

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled technical architect with a strong background in custom systems, AI infrastructure, and automation. However, this role requires a functional architect with specific, hands-on expertise in Workday Financials, HCM, and the Asset Management domain, none of which are present in the candidate's experience. **⚠️ Critical Gaps:** - Candidate's experience is in technical/infrastructure architecture (building custom systems with Python, AI, Docker), while the role requires a functional architect for a SaaS platform (Workday). **✅ Strengths:** - Proven Fast Learner & Self-starter - Strong Technical Systems Background - Connects Business Logic to Technical Implementation **❌ Missing Required:** Workday Financial Management, Workday Reports, Workday HCM, Asset and Wealth Management

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] This is a poor fit. The candidate has impressive experience in systems architecture, automation, and AI infrastructure, but possesses no stated experience in the required domains of ITOM, ITSM, or the ServiceNow platform, which are the core of the role. The candidate's skills, while strong, are in a completely different domain and the lack of required certifications is a hard filter. **⚠️ Critical Gaps:** - ITOM Experience - ITSM Experience - ServiceNow Platform Experience **✅ Strengths:** - Strong transferable skills in scripting (Python/Shell) and creating business logic. - Proven ability to learn and implement complex technical systems from scratch. - Deep experience with automation and systems integration, albeit in a different context. **❌ Missing Required:** CSA Certification, CIS ITOM Certification, Experience with any ServiceNow functionality (Discovery, Service Mapping, Incident Management, etc.)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate shows strong foundational skills in infrastructure automation (Terraform, CI/CD) and containerization (Docker), which are highly relevant. His background in finance and experience architecting production systems are significant strengths, but the score is limited by a clear lack of demonstrated experience with the required Google Cloud Platform (GCP) services. **✅ Strengths:** - Hands-on experience with core infrastructure tools (Docker, Terraform, CI/CD) - Proven ability to architect and build production systems from scratch - Relevant domain experience in high-stakes financial systems **❌ Missing Required:** Experiência no desenho de soluções na GCP, Vivência com segurança em múltiplos níveis (GCP)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems engineer with proven experience in infrastructure automation (Terraform, Docker) and complex project delivery (JIT system, AI clusters). However, there is a significant gap between his hands-on, implementation-focused background and the job's requirement for a senior architect fluent in formal methodologies like Domain-Driven Design, microservice patterns (EDA, CQRS), and specific cloud-native observability tools (Prometheus, Jaeger). While he demonstrates exceptional learning ability, he lacks direct experience with the specified high-level architectural practices. **⚠️ Critical Gaps:** - Lacks demonstrated experience in formal software architecture paradigms (DDD, Clean Architecture, EDA) which is central to the role. - Missing deep proficiency in cloud-native ecosystems (Kubernetes, advanced AWS/GCP, observability tooling) required for a senior architect. **✅ Strengths:** - Proven ability to architect and build complex, automated systems from scratch (JIT Inventory). - Strong hands-on infrastructure skills (Docker, Terraform, Self-Hosted AI Clusters). - Exceptional learning velocity and initiative, moving from Finance to AI Infrastructure. - Deep expertise in Python for automation and data-intensive tasks. **❌ Missing Required:** Microservices, Event-driven architectures (Kafka, RabbitMQ), Kubernetes, Advanced Cloud Proficiency (AWS/GCP/Azure), Observability Tooling (Prometheus, Jaeger), Domain-Driven Design (DDD), Scalability Patterns (Caching, Load Balancing)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a strong conceptual match, with proven experience architecting complex data systems from the ground up. While lacking explicit keywords for AWS Glue, Spark, and Redshift, his background in building automated inventory and AI infrastructure demonstrates mastery of the underlying ETL, data processing, and warehousing principles. The 'Fast Learner' profile and direct experience in the financial domain make him a high-potential candidate despite the resume's modest 'AWS Basics' keyword. **✅ Strengths:** - Proven Systems Architect - Deep Python Expertise for Data - Financial Domain Background **❌ Missing Required:** Advanced AWS Services (resume lists 'AWS Basics'), AWS GLUE, Apache Spark, Amazon Redshift

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems builder with proven "metal-up" architectural talent and an impressive fast-learner track record. However, there is a critical gap between their hands-on, self-hosted infrastructure experience (Docker, local AI clusters) and the job's requirement for deep, enterprise-scale cloud-native architecture, specifically mentioning Kubernetes and extensive cloud migration expertise (AWS/Azure/GCP). **⚠️ Critical Gaps:** - Lacks container orchestration (Kubernetes) and deep cloud computing experience (only AWS Basics listed), which are central to the role's cloud migration and modernization duties. **✅ Strengths:** - Proven ability to architect, build, and deploy complex, automated systems from scratch. - Strong Python and infrastructure automation skills. - Demonstrated "fast learner" capability, successfully entering new technical domains like AI infrastructure. **❌ Missing Required:** Experience with Java/Go and their main frameworks (Springboot, Quarkus), Knowledge in observability (SLA, SLI, SLO), Container orchestration (Kubernetes, EKS)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong systems architect with proven, hands-on experience in core requirements like Terraform, Docker, CI/CD, and security. The high score reflects deep conceptual alignment and a demonstrated ability to build complex systems from the ground up. The primary gaps are the lack of Java/Spring Boot experience and a self-assessed 'basic' knowledge of AWS versus the required 'advanced' expertise. **⚠️ Critical Gaps:** - Required hands-on development for PoCs is in Java/Spring Boot, while the candidate's extensive experience is exclusively in Python. **✅ Strengths:** - Direct, hands-on experience with core infrastructure-as-code (Terraform) and containerization (Docker). - Proven ability to architect, build, and deploy complex, automated production systems from scratch. - Excellent career trajectory demonstrating progression towards complex systems architecture and AI. **❌ Missing Required:** Expertise avançada em AWS (candidate self-reports 'AWS Basics'), Desenvolvimento hands-on em Java/Spring Boot, Observabilidade: CloudWatch, X-Ray, Prometheus, Grafana, ELK/Opensearch, Dynatrace/Datadog

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidato forte em arquitetura de sistemas e automação, alinhado à visão 'do metal para cima' do cargo. Apresenta lacunas em Kubernetes e Observabilidade, que são requisitos diretos, mas demonstra rápida capacidade de aprendizado e possui conhecimento em IaC (Terraform) e nuvem (AWS básico). **✅ Strengths:** - Arquitetura de Sistemas (Visão Sistêmica) - Automação de Processos (Python/Scripting) - Infraestrutura como Código (Terraform) **❌ Missing Required:** Kubernetes, Observabilidade, Experiência aprofundada em nuvem pública (além do básico)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate's profile is a complete mismatch for the role. The job requires deep, specialized experience in a legacy IBM Mainframe environment (COBOL, CICS, DB2 for z/OS), while the candidate's entire expertise and career trajectory are focused on modern cloud and AI infrastructure (Python, Go, Docker, AWS, Self-hosted LLMs). There is zero overlap in the core required technologies. **⚠️ Critical Gaps:** - Mainframe Development & Administration (COBOL, CICS, z/OS) - DB2 for Mainframe Ecosystem **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex domains - Strong modern systems architecture and automation background - Fluent English **❌ Missing Required:** IBM DB2 FOR Z/OS, COMPUWARE FILE-AID DB2, Experiência comprovada com DB2 na plataforma baixa (Windows e Linux)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong match. Their career trajectory from Systems Architecture to AI Infrastructure aligns perfectly with the role's focus on modern cloud solutions and developer autonomy. Key required skills like Linux, Python, CI/CD, and containerization are strongly demonstrated or inferred from complex, recent projects like self-hosting LLM clusters. **✅ Strengths:** - Ideal career trajectory progressing towards this exact role - Proven ability to self-teach and master complex, relevant infrastructure (AI Clusters) - Demonstrated experience in CI/CD, cloud (AWS), and containerization **❌ Missing Required:** Windows

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is a highly capable systems architect with strong business acumen and a proven ability to self-teach complex technologies. However, there is a critical gap, as they possess no demonstrated experience with Adobe Analytics or similar product/marketing analytics platforms, which is the core requirement of the role. **⚠️ Critical Gaps:** - Lacks experience in the entire domain of product/marketing analytics suites (e.g., Adobe Analytics). Candidate's experience is in backend, infrastructure, and financial/supply-chain data, not customer-facing product analytics. **✅ Strengths:** - Strong business acumen translating goals to technical systems - Proven fast learner with a track record of mastering new domains (AI, trading) - E-commerce domain experience **❌ Missing Required:** Adobe Analytics, 5-7 years in product/client analytics strategy, Experience with tools like Amplitude, Mixpanel, Google Analytics, Creating analytics tracking specifications for web/mobile

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect and Backend/Infrastructure Engineer with a proven ability to self-teach complex domains. However, this role is for a Technical Project Manager with a mandatory strong background in frontend technologies and formal Agile/Scrum team leadership. There is a critical and fundamental domain mismatch between the candidate's deep infrastructure expertise and the job's frontend and agile project management requirements. **⚠️ Critical Gaps:** - Frontend development experience (the job requires strong knowledge of Flutter, React, or Stencil.JS, and the candidate has none) **✅ Strengths:** - Exceptional self-learner with proven track record in AI and quantitative systems - Deep experience in systems architecture and end-to-end automation - Strong technical foundation in backend and infrastructure (Python, Docker, Cloud) **❌ Missing Required:** Solid experience in leading & managing multiple complex projects in agile environments (Scrum and Kanban), Experience in Project Management Tools such as Jira, Experience in the frontend environment

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a very strong technical fit with hands-on experience in building and deploying complex systems, including self-hosted Generative AI models. The career trajectory shows a clear and intentional progression toward this exact type of role. The primary gap is the required 4+ years of direct, continuous client engagement, as recent experience has been more internally focused. **✅ Strengths:** - Hands-on Generative AI/LLM experience - Systems architecture from 'metal-up' - Proven fast learner with strong Python skills **❌ Missing Required:** 4+ years of technical client engagement

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] Candidato desqualificado devido a um desalinhamento geográfico. A vaga exige presença híbrida em Brasília/DF, enquanto o candidato reside em São Paulo. Tecnicamente, ele é um forte arquiteto de automação e IA, mas possui uma lacuna crítica na falta de experiência com plataformas de RPA, que é o requisito central da vaga. **⚠️ Critical Gaps:** - Experiência com plataformas de RPA (UiPath, Automation Anywhere, Power Platform) - Requisito de localização (Híbrido em Brasília/DF) **✅ Strengths:** - Arquitetura de Sistemas de Automação em Larga Escala - Infraestrutura de IA (Clusters de LLM auto-hospedados) - Desenvolvimento avançado em Python para automação e análise **❌ Missing Required:** 6+ anos de experiência em desenvolvimento RPA, Process Mining + IA, Experiência com OCR (Abby, Tesseract, etc.), Metodologias ágeis

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is a strong systems architect and proven fast learner but has critical gaps in the core required technologies (C#/.Net, JavaScript/Angular). Their experience is in a completely different domain (Python, AI/Infrastructure), making them a poor fit for this specific framework development role. **⚠️ Critical Gaps:** - Deep Expertise in C# and .Net - Expertise in JavaScript and Angular **✅ Strengths:** - Systems architecture design - Proven ability to learn complex new domains - Strong communication and business-to-technical translation skills **❌ Missing Required:** C#, .Net, JavaScript, Angular

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven systems architect and a fast learner with strong skills in automation, Python, and infrastructure, but has a critical domain gap. There is zero demonstrated experience in the required mobile telecommunications field (LTE, 5G, IMS, 3GPP standards), making this a very poor fit for a specialized Network Architect role. **⚠️ Critical Gaps:** - Mobile Telecom Network Architecture (GSM/UMTS/LTE/IMS/5G) **✅ Strengths:** - Complex Systems Architecture from scratch - Advanced Python-based Automation - Proven Fast Learner in new technical domains **❌ Missing Required:** Proven experience in mobile telecom networks, Knowledge of 3GPP, GSMA, ITU standards, Experience with Packet Core systems (P-GW, PCRF, etc.), Experience with roaming interconnects (GRX/IPX), Experience deploying VoLTE/VoWiFi, Knowledge of telecom protocols (Diameter, GTP, MAP), Experience with ETSI NFV architecture

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is fundamentally mismatched for this role. The position requires a degree in Architecture and experience in interior design with Revit software. The candidate's background is in Mechatronics Engineering, software development, and AI infrastructure, which is a completely different domain. **⚠️ Critical Gaps:** - Domain Mismatch: Candidate's experience is in Technology/AI, not Civil Architecture or Interior Design. **✅ Strengths:** - AI Infrastructure Deployment - Automated Systems Design (JIT) - Python Development **❌ Missing Required:** Bachelor's in Architecture, 3+ years of experience in Interior Architecture, Proficiency in Revit

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a strong match with deep, hands-on experience in architecting complex automated systems and self-hosting AI/LLM infrastructure. The career trajectory shows a deliberate move into this domain. The main gap is a lack of stated experience with specific multi-agent frameworks, though this is likely easy to learn given the candidate's proven fast-learner track record. **✅ Strengths:** - Hands-on LLM infrastructure experience (self-hosted) - Proven ability to architect and build complex, automated production systems from scratch - Deep Python and automation skills applied to real-world business problems **❌ Missing Required:** LangChain, CrewAI, AutoGen

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong fit, bordering on overqualified. He demonstrates deep, practical experience in building and deploying complex automated systems, including self-hosted LLMs which directly maps to the NLP focus. His background in Python, production systems (Docker), and data analysis is evident from his projects, even without a formal "Data Scientist" title. **✅ Strengths:** - Hands-on AI infrastructure experience (self-hosted LLMs) - Proven ability to build and deploy automated, production-grade systems from scratch - Strong, applied Python and data analysis skills in real-world projects (trading, logistics)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong fit, demonstrating deep, practical experience in designing and building complex systems, including self-hosted LLM infrastructure. His background in Python, systems architecture, and finance aligns perfectly with the role's requirements and nice-to-haves. The single minor gap is a lack of stated experience with specific frameworks like TensorFlow/Keras, which is heavily mitigated by his proven fast-learner track record. **✅ Strengths:** - Hands-on AI/LLM Infrastructure Experience - Advanced Python for Backend & Systems Architecture - Proven Fast Learner with Relevant Financial Domain Experience **❌ Missing Required:** Modelos e frameworks de Deep Learning (ex.: TensorFlow, Keras)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a very strong fit, demonstrating deep, hands-on experience in building and architecting complex systems, including self-hosted AI infrastructure. The career trajectory shows a deliberate and successful progression toward this exact type of role. The only significant gap is the lack of explicit experience with Amazon SageMaker, which is mitigated by a proven fast-learning ability and strong foundational knowledge. **✅ Strengths:** - Deep 'metal-up' systems architecture experience - Proven ability to build and deploy complex automated systems from scratch - Strong career trajectory demonstrating intentional growth into AI infrastructure **❌ Missing Required:** Amazon SageMaker

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable Systems Architect with strong, demonstrated skills in custom automation, system design, and Python. However, there is a critical and disqualifying gap in the core requirement for this role: zero experience or certification in enterprise RPA platforms like Automation Anywhere. While he is a proven fast learner, the absence of the primary required technology makes him a poor fit without significant retraining. **⚠️ Critical Gaps:** - Experience with any enterprise RPA platform (e.g., Automation Anywhere, UiPath) - Master Certification in Automation Anywhere or similar **✅ Strengths:** - Proven ability to architect and build complex automation systems from scratch - Deep experience in Python for automation and data analysis - Strong career trajectory towards complex technical and architecture roles **❌ Missing Required:** Certificação Master na ferramenta Automation Anywhere ou similar

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] O candidato possui uma base excepcional em arquitetura de sistemas, automação com Python e infraestrutura de IA, demonstrada pela criação de clusters LLM próprios. No entanto, há uma lacuna crítica na experiência com as ferramentas específicas do ecossistema Microsoft (Power Automate, Copilot Studio, C#), que são o foco principal da vaga. **⚠️ Critical Gaps:** - Falta de experiência comprovada no ecossistema Microsoft Power Platform (Power Automate, Copilot Studio, Power Fx). - Ausência das linguagens de programação mandatórias: C# e JavaScript/TypeScript. **✅ Strengths:** - Profundo conhecimento em infraestrutura de IA (clusters LLM auto-hospedados) - Experiência comprovada em automação de processos de ponta-a-ponta (sistema JIT) - Forte background em arquitetura de sistemas e resolução de problemas complexos **❌ Missing Required:** Microsoft Copilot Studio, Power Automate, UiPath, Blue Prism, C#, JavaScript/TypeScript, Power Fx, Azure OpenAI

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is a highly skilled systems architect with deep experience in building backend automation and AI infrastructure. However, he is a poor fit due to a critical geographic mismatch (job is on-site in Campinas, candidate is in São Paulo) and a domain gap. The role requires applying business automation tools (n8n, Chatwoot, WhatsApp), whereas the candidate's experience is in building core infrastructure (LLM clusters, custom logistics). **⚠️ Critical Gaps:** - Geographic Mismatch: Job requires on-site work in Campinas, candidate is based in São Paulo. - Role Mismatch: Candidate is an Infrastructure Architect, while the job is for a Business Automation Integrator using specific SaaS tools. **✅ Strengths:** - Deep expertise in automation and scalable systems architecture - Proven 'Fast Learner' with a strong track record of self-teaching complex technical domains - Experience with Generative AI (self-hosted LLMs) and building production systems **❌ Missing Required:** Domínio de WhatsApp Web e WhatsApp Oficial, Vivência com Chatwoot, Evolution, n8n ou ferramentas similares, Trabalhar com tickets, SLA, engajamento e conversão

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] O candidato é um engenheiro de sistemas e automação muito competente, com forte experiência em Python e na construção de infraestrutura. No entanto, ele apresenta lacunas críticas em fundamentos de engenharia de dados para análise, como Data Warehousing, modelagem dimensional e SQL avançado, que são centrais para esta função. Apesar de sua capacidade de aprendizado rápido, a falta de correspondência com as habilidades principais o torna um ajuste fraco (POOR_FIT). **⚠️ Critical Gaps:** - Experiência fundamental em Engenharia de Dados para Analytics (Data Warehousing, Modelagem Dimensional, SQL Analítico) **✅ Strengths:** - Forte experiência em Python para automação e pipelines de dados operacionais - Capacidade comprovada de autoaprendizagem e adaptação a novas tecnologias (Fast Learner) - Experiência prática na arquitetura e construção de sistemas de produção complexos do zero **❌ Missing Required:** Domínio de SQL avançado (joins, funções de janela, CTEs), Conhecimento sólido em conceitos de Data Warehouse e modelagem dimensional, Familiaridade com práticas de qualidade de dados, linhagem, governança, Vivência com ferramentas de descoberta e catalogação de dados (Amundsen ou similares), Conhecimento em modelagem de dados para relatórios e dashboards (Power BI ou similares)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a strong architectural fit with deep, demonstrated experience in Python, systems design, and cloud infrastructure, aligning perfectly with the core engineering and leadership duties. The profile shows a clear progression towards this type of role. The main gaps are specific tools (Airflow, Power BI), which are considered learnable given the candidate's proven fast-learning track record. **✅ Strengths:** - Systems Architecture & Design - Python for Automation & Data - Cloud & On-Prem Infrastructure Leadership **❌ Missing Required:** Apache Airflow, Power BI

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong conceptual match with deep, proven experience in systems architecture and self-hosting AI infrastructure from the ground up. While lacking direct experience with the specified cloud platforms (GCP/Azure) and agent frameworks (LangChain/CrewAI), his demonstrated ability to self-teach and build complex production systems makes him a low-risk, high-potential candidate. **✅ Strengths:** - Deep AI Infrastructure Knowledge (Self-hosted LLMs) - Proven Systems Architecture (Automated JIT System) - Strong Python & Automation Skills **❌ Missing Required:** Experiência sólida em Microsoft Azure, Vivência com Google Cloud Platform (GCP), Domínio de desenvolvimento de agentes autônomos com frameworks (LangChain, CrewAI, Autogen), Experiência com avaliação e segurança de IA Generativa (RAGAS, NeMo Guardrails)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is automatically disqualified as this is an affirmative action position exclusively for people with disabilities (PCD), and the candidate's profile indicates they do not have a disability. While the technical skills are a strong match for the underlying roles, the candidate does not meet the non-negotiable demographic requirement for this specific talent pool. **⚠️ Critical Gaps:** - Does not meet the mandatory affirmative action requirement for people with disabilities (PCD). **✅ Strengths:** - Career trajectory towards Systems Architecture and AI Infrastructure aligns with the technical domains. - Proven fast learner with a track record of self-teaching complex systems. - Fluent in English, which is valuable for technical roles. **❌ Missing Required:** Affirmative action requirement: Person with disability (PCD)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with proven automation skills and fluent English. However, they lack explicit experience in QA roles and, critically, in designing the reusable testing frameworks required by the job. Their background is in building operational systems, not QA frameworks. **⚠️ Critical Gaps:** - Lacks experience in creating testing and automation frameworks, which is the core responsibility of the role. **✅ Strengths:** - Advanced English - Proven experience in building complex automation systems - Strong self-learner with a technical trajectory towards complex systems **❌ Missing Required:** Experience in QA for software (manual), Experience designing and implementing test cases

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong technical architect with a background in analytics and systems automation, but this role is for an operational, client-facing team supervisor. The candidate's career trajectory is moving decisively away from the core functions of this job, creating a significant mismatch in experience and career goals. **⚠️ Critical Gaps:** - Supervisão de equipes operacionais (Team Supervision) - Gestão de carteira de clientes (Client Account Management) **✅ Strengths:** - KPI & Performance Analysis - Process Improvement Identification - Fast Learner with Strong Technical Acumen **❌ Missing Required:** 3+ years experience supervising teams, Client-facing account management experience, Educational background in Business Administration or Commercial Management

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate possesses exceptional technical and data analysis skills, particularly with financial and unstructured data from his time as an analyst and trading bot developer. However, his profile is that of a deep technical architect, not a client-facing project manager. There is a significant gap in demonstrated experience managing external client implementations and onboarding, which is the core function of this role. **⚠️ Critical Gaps:** - Lack of demonstrated experience in a primarily client-facing project management role. **✅ Strengths:** - Deep understanding of financial data and systems - Proven ability to interpret stories from unstructured data (Analytics/Trading) - Strong technical architecture and problem-solving skills **❌ Missing Required:** Proven success in a project management capacity (client-facing), Experience working with clients (at enterprise scale)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong fit, demonstrating extensive experience shipping production-quality code using Python, a required language. Their recent role involved architecting and building a complex, automated backend system from scratch, which directly aligns with the job's core need for API and backend design expertise. The candidate's clear career progression towards systems architecture and proven ability to self-teach complex domains (like AI infrastructure) make them a top-tier applicant. **✅ Strengths:** - Deep Python expertise applied to production systems - Proven ability to architect and build end-to-end backend solutions - Strong career trajectory and demonstrated 'Fast Learner' capability

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong match, demonstrating deep expertise in Python, SQL, and system automation. Crucial MLOps capabilities are strongly inferred from their experience building production-grade automated systems and self-hosting LLMs. The primary gap is a lack of stated experience with data visualization tools. **✅ Strengths:** - End-to-end System Architecture - Python-based Automation & API Integration - Infrastructure Deployment (Self-hosted LLMs) **❌ Missing Required:** Data visualization tools (Looker Studio, Power BI, Tableau)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with impressive self-taught skills in AI infrastructure and automation. However, the role's core requirements of managing both backend and frontend software teams and using agile methodologies are not demonstrated in their experience, which focuses more on solo-led, backend-heavy projects. **⚠️ Critical Gaps:** - Frontend development/leadership experience **✅ Strengths:** - Deep systems architecture knowledge - Proven fast learner with AI/infra skills - Strong backend and automation experience with Python **❌ Missing Required:** Managing software development teams, Agile methodologies

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong fit. His hands-on experience in architecting and deploying complex automated systems, including self-hosting AI models, directly aligns with the 'AI Operations' title. His career trajectory and proven ability to self-teach and master new technical domains suggest he would excel in a dynamic, project-based AI ecosystem. **✅ Strengths:** - Deep, practical experience with AI infrastructure (self-hosted LLMs) - Proven ability to architect and automate complex systems from scratch (JIT inventory) - Strong sense of ownership and process optimization demonstrated by founding an automated business

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate's profile is a severe mismatch for this role. His expertise is in highly technical domains like AI infrastructure, systems architecture, and software engineering, whereas the job requires administrative and legal expertise in Human Resources, specifically payroll and Brazilian labor law. There is no overlap in skills or career trajectory. **⚠️ Critical Gaps:** - The candidate is a Systems/AI Engineer, while the role is a non-technical Human Resources Payroll Analyst. The domains are completely unrelated. **✅ Strengths:** - Proven fast learner in technical domains - Strong automation and systems-building mindset - Data analysis proficiency **❌ Missing Required:** Legislação Trabalhista (Brazilian Labor Law), Experiência com Folha de Pagamento (Payroll Experience), Conhecimento em Administração de Pessoal (Personnel Administration Knowledge)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] O candidato é desqualificado devido à falta de uma certificação legalmente exigida (NR 10). Além disso, há uma incompatibilidade fundamental entre o perfil do candidato (Arquiteto de Sistemas Sênior e especialista em IA) e a natureza da vaga (suporte administrativo e técnico de campo júnior). **⚠️ Critical Gaps:** - A ausência da Certificação NR 10 é um filtro eliminatório, pois é um requisito legal para a função. - O candidato é um arquiteto de sistemas de alto nível; a vaga é para suporte técnico de campo, representando domínios de trabalho completamente diferentes. **✅ Strengths:** - Capacidade comprovada de aprendizado rápido e auto-didatismo. - Experiência em design de sistemas complexos e automação. - Fluência em Inglês. **❌ Missing Required:** Certificação NR 10, Leitura e interpretação de desenho elétrico e mecânico

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate possesses exceptional analytical and problem-solving skills but is a severe functional mismatch for this junior-level role. His career trajectory shows a clear and intentional progression away from business analysis and towards deep, senior-level systems architecture and AI infrastructure. The core domain of 'Cobrança' (Collections) is entirely absent from his experience, representing a critical gap. **⚠️ Critical Gaps:** - Domain Experience: Candidate has zero background in 'Cobrança' (Collections), which is the core function of this role. **✅ Strengths:** - Exceptional analytical and problem-solving capabilities demonstrated through complex system design. - Proven 'Fast Learner' with a track record of mastering new, difficult domains (AI, Algorithmic Trading). - Advanced technical skills for data manipulation (Python, SQL). **❌ Missing Required:** Experience in strategic planning or MIS specifically related to financial services or call center operations.

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit due to a critical gap in front-end skills (JavaScript/React) and a complete lack of experience in the required Java/Kotlin/Spring ecosystem. While they have outstanding strengths in backend architecture, Python automation, and AI infrastructure, these do not align with the core requirements of this full-stack Java developer role. **⚠️ Critical Gaps:** - Front-End Development (JavaScript, React.js) is required, but candidate experience is exclusively Backend/Infrastructure. **✅ Strengths:** - Systems Architecture & Integration - Python Automation & Data Processing - AI/LLM Infrastructure Deployment **❌ Missing Required:** Java, Kotlin, Spring/SpringBoot, JavaScript (3+ years), React.js

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and automation engineer but has critical gaps in all required domain knowledge. There is no demonstrated experience in billing systems (SAP/CCS), the energy sector, or specific regulatory frameworks like REN 1000 ANEEL. His strengths are in general IT integration and systems design, but not in the specific business area of this role. **⚠️ Critical Gaps:** - Billing Systems (SAP/CCS, etc.) - Energy Sector Experience **✅ Strengths:** - Systems Architecture & Design - API Integration - Process Automation (Python) **❌ Missing Required:** Conhecimento da REN 1000 ANEEL, Conhecimento de processos de medição, cálculo, faturamento e emissão de faturas

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a near-perfect fit. He demonstrates exceptional, hands-on experience architecting and deploying automated, secure, production-grade systems from the ground up, which aligns directly with the core responsibilities of a DevSecOps Architect. While lacking explicit keywords for the specific toolchain (GitLab, ArgoCD), his resume lists 'CI/CD Pipelines', 'Terraform', and 'Docker', proving mastery of the underlying principles (IaC, containerization, automation) and making the specific tools a minor, easily-surmounted learning curve. **✅ Strengths:** - Deep, Practical Experience in Systems Architecture - Proven Mastery of Automation and CI/CD Principles - Strong Security Mindset (Privacy-first, SSO, RBAC) **❌ Missing Required:** GitLab, ArgoCD, SonarQube

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate exhibits strong architectural and systems-thinking skills, with proven experience in building complex, automated systems from scratch using Python and Docker. However, there is a critical gap in the primary required languages (Golang/Typescript) and a lack of demonstrated experience with key technologies like Kafka and monitoring tools. **⚠️ Critical Gaps:** - Required language is Golang or Typescript; candidate's experience is exclusively in Python. **✅ Strengths:** - Systems Architecture & Design - Python Automation - Infrastructure & Containerization (Docker) **❌ Missing Required:** Event Streaming (Kafka), Monitoring & Observability, Unit & Integration Testing

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate possesses a relevant engineering degree and strong technical project leadership, but there is a critical domain gap. His experience is in IT systems, e-commerce automation, and AI infrastructure, whereas the role requires specific expertise in automotive embedded electronics and OEM project management. **⚠️ Critical Gaps:** - Automotive Industry Experience - Embedded Electronics Project Management **✅ Strengths:** - Strong Engineering Background (Mechatronics) - Proven Fast Learner & Self-Taught in Complex Tech (AI) - Fluent English

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect with deep, modern infrastructure skills (Docker, Python, AI Clusters), but has a critical gap in hands-on corporate network management (firewalls, switches). While likely overqualified in architecture, he lacks experience in key administrative duties of the role like license and mobile device management, making it a poor fit despite his technical talent. **⚠️ Critical Gaps:** - Hands-on corporate networking (firewalls, switches) vs. modern cloud/AI-cluster networking **✅ Strengths:** - Proven Systems Architecture Design - Strong Automation & Scripting Skills (Python) - Fast Learner with Diverse Tech Experience **❌ Missing Required:** gestão de licenças de softwares e hardwares, manutenções em firewall, switches

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Lite] The candidate's resume was empty, preventing verification of essential requirements such as a Bachelor's degree and proficiency in Google Sheets/Excel. While the candidate meets the English language requirement and the provided context indicates a strong "Fast Learner" profile, the absence of resume data creates significant gaps. **✅ Strengths:** - English Proficiency (C2) - Fast Learner Profile - Strong Career Trajectory (provided context) **❌ Missing Required:** Bacharelado em Engenharia ou Arquitetura, Proficiência avançada em Google Sheets/Excel

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Lite] The candidate's resume is empty, preventing any assessment of demonstrated skills or experience. A critical gap exists in the required Mainframe/COBOL expertise, and the candidate's background suggests a trajectory away from legacy systems towards modern AI. While English proficiency is met, the lack of experience and a degree are disqualifying. **⚠️ Critical Gaps:** - Mainframe / COBOL environments - Bachelor’s degree in Engineering, Computer Science, Information Systems or related fields **❌ Missing Required:** Mainframe / COBOL environments, Systems development and troubleshooting in Mainframe / COBOL, Application support, incident analysis and vendor interaction, Lead technical topics and orchestrate stakeholders, Strategic mindset toward incident prevention and continuous improvement, Bachelor’s degree in Engineering, Computer Science, Information Systems or related fields

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Lite] The candidate's resume is empty, providing no information to assess their qualifications, experience, or skills against the job requirements for a Systems Coordinator in e-commerce. **⚠️ Critical Gaps:** - No verifiable qualifications from resume **❌ Missing Required:** Ensino superior completo em TI, Sistemas de Informação, Logística, Engenharia ou áreas correlatas, Experiência prévia em e-commerce e em operações fullcommerce ou similares, Vivência com gestão de equipes técnicas, Conhecimento consolidado em sistemas de backoffice: ERP, WMS e plataformas de e-commerce, Entendimento profundo do fluxo operacional 360 do e-commerce, Familiaridade com processos logísticos, Capacidade analítica e domínio de Excel avançado, Visão de projeto e organização, Experiência com ERP KPL, Conhecimentos em VTEX, Familiaridade com WMS SILT, Experiência com integrações via XML, JSON, APIs, Noções de banco de dados SQL

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Lite] The candidate demonstrates a strong technical foundation in infrastructure, evidenced by their Systems Architecture and AI Infrastructure roles, and a remarkable ability to learn and build complex systems. They show clear progression toward IT infrastructure domains, with strong inferred skills in on-premises and cloud environments. However, explicit experience in formal project management methodologies (PMI) and specific areas like service transition is missing, which are key requirements for an Infrastructure Project Manager. **✅ Strengths:** - Strong technical understanding and inferred skills in on-premises and cloud infrastructure. - Demonstrated ability to learn and execute complex technical projects. - Exceptional learning agility and continuous education drive. **❌ Missing Required:** Sólida experiência em gerenciamento de projetos de infraestrutura de TI, com domínio das melhores práticas do PMI., Experiência em Transição de Serviços e implementação de modelos de Serviços Gerenciados.

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Lite] The candidate demonstrates a very strong alignment with the job requirements, showcasing excellent technical skills in Python, cloud platforms, and containerization, coupled with a compelling career trajectory towards AI infrastructure. While SQL proficiency is noted as a gap, their inferred skills and proven fast-learning ability make them a top-tier candidate. **✅ Strengths:** - Strong technical foundation and rapid learning ability, evidenced by self-taught AI/ML infrastructure and successful career transitions. - Proficiency in Python and related AI/ML infrastructure (LLM clusters), cloud platforms (AWS), and containerization. - Implied Bachelor's degree and demonstrated capability for enterprise-level data engineering tasks. **❌ Missing Required:** SQL