[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidato excepcional para vagas de infraestrutura de IA, arquiteto de software e SRE/DevOps. Demonstra uma rara combinação de arquitetura de sistemas de ponta a ponta (sistemas JIT automatizados) e experiência prática na implantação de infraestrutura de IA complexa (clusters de LLM auto-hospedados). A sua trajetória de carreira demonstra uma progressão deliberada e bem-sucedida em direção a papéis técnicos de alta complexidade. **⚠️ Critical Gaps:** - Nenhuma para as áreas de IA, Infraestrutura, Arquitetura ou Back-end Python. Lacuna crítica em desenvolvimento Front-End para uma posição Full Stack. **✅ Strengths:** - Expertise em Infraestrutura de IA (implantação de LLMs em hardware local) - Arquitetura de Sistemas comprovada (criação de sistemas automatizados de ponta a ponta) - Profundo conhecimento prático em Python aplicado a domínios complexos (Finanças, Logística) **❌ Missing Required:** Nenhuma habilidade requerida ausente para as áreas de melhor fit (IA, DevOps, Arquitetura). Faltam linguagens específicas (Java, Go, C#) para outras posições de back-end.

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong match due to a clear career progression into Systems Architecture, which directly aligns with the role's core requirement. The demonstrated ability to self-teach and build complex systems like self-hosted LLM clusters strongly infers the necessary skills for a modern solutions architect. **✅ Strengths:** - Career trajectory shows intentional progression directly into Systems Architecture. - Proven fast learner with deep, self-taught knowledge in complex, relevant domains (AI infrastructure). - Experience spans multiple business areas, providing a broad context for solution design.

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong conceptual architect with excellent DevOps, systems integration, and business analysis skills that align with the role's high-level goals. However, there is a critical, blocking gap: the candidate has zero demonstrated experience with the entire required .NET technology stack, which is the core of this position. Their background is exclusively in a different ecosystem (Python, Linux, OSS). **⚠️ Critical Gaps:** - Entire .NET ecosystem (.Net Core, ASP.NET, Entity Framework, etc.) **✅ Strengths:** - Exceptional DevOps and CI/CD background - Strong Systems Architecture and design skills - Proven experience translating business logic into technical solutions **❌ Missing Required:** .Net Core, ASP.NET Core, MSTEST, Entity Framework

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] This is a complete domain mismatch. The candidate is a Systems/Infrastructure Architect specializing in IT, automation, and AI, while the job requires a licensed Building/Construction Architect with expertise in Revit, BIM, and the hospitality real estate sector. The candidate possesses none of the required core skills or educational background. **⚠️ Critical Gaps:** - The candidate's experience is in IT Systems Architecture, not building/construction architecture, which is a fundamentally different profession. - Candidate lacks the required Bachelor's or Master's Degree in Architecture. - Candidate has zero experience with required software (Revit, Navisworks, BIM) or industry processes (RIBA stages). **✅ Strengths:** - Fluent in English - Proactive and independent problem-solver - Experience in a remote work environment **❌ Missing Required:** Bachelor's or Master's Degree in Architecture, 5 to 10 years of experience in architectural design, Proficiency in Revit, Proficiency in Navisworks, Experience on low-rise residential and hospitality projects, Architectural portfolio

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable Systems Architect with impressive, demonstrated skills in AI infrastructure and full-system automation. However, there is a critical and disqualifying gap: the complete absence of Salesforce experience, which is the core requirement of the role. The candidate's strengths are in a different technical domain. **⚠️ Critical Gaps:** - The role requires a Salesforce Architect, but the candidate has no demonstrated experience in the Salesforce ecosystem. This is a fundamental domain mismatch. **✅ Strengths:** - Advanced AI & LLM Infrastructure Experience - Proven ability to design and build complex, automated systems from scratch - Strong background connecting business logic (Finance, Supply Chain) to technical implementation **❌ Missing Required:** System Architect certification (indispensable), Experience with Salesforce-specific technologies (Apex, LWC, etc.), Knowledge of Salesforce integration models and best practices, Experience with Salesforce Data Modeling and Management

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate possesses strong, demonstrated skills in systems architecture, automation, and infrastructure (Docker, AWS, CI/CD), which align with the role's leadership aspects. However, there is a critical and disqualifying gap in the core technology stack, as the role requires deep expertise in PHP and Vue.js, neither of which are present in the candidate's background. **⚠️ Critical Gaps:** - PHP (Required 'sólida experiência', but candidate has none) - Vue.js (Required in stack, but candidate has no frontend experience) **✅ Strengths:** - Systems Architecture & Design - Automation & CI/CD Pipelines - Infrastructure Management (Docker, AWS) **❌ Missing Required:** DDD, SOLID, Clean Architecture, Vivência em transformação de arquiteturas monolíticas, Redis

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is a complete mismatch for this role. The position requires a degree and experience in Architecture and civil construction, specifically with hospitals. The candidate's entire background is in Software Engineering, AI, and Finance, with no transferable skills applicable to this specific job. **⚠️ Critical Gaps:** - Candidate's domain is Software/AI, while the job is in Architecture/Civil Construction. **✅ Strengths:** - Proven ability to learn complex subjects quickly - Strong systems architecture background in an unrelated field (IT) - Fluent English **❌ Missing Required:** Curso superior completo em Arquitetura, Experiência com obras verticais, Experiência na construção de hospitais, Conhecimento de Autocad

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate possesses a strong background in systems architecture and is a proven fast learner. However, there is a critical domain gap, as their entire expertise is in the Python/AI/Infrastructure ecosystem, while the role is strictly for a senior Java Enterprise Architect. **⚠️ Critical Gaps:** - The candidate's experience is entirely in the Python/AI ecosystem, whereas the role is for a Java Enterprise Architect. This represents a fundamental mismatch in core programming language and platform expertise. **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex domains. - General experience in Systems Architecture. - Fluent in English and native in Portuguese. **❌ Missing Required:** Formação superior em informática ou certificação java ee architect, Experiência comprovada como arquiteto de aplicações java ee e/ou spring, Experiência com servidores de aplicação java (tomcat, jboss, websphere), Habilidade em ibm integration bus, ibm websphere mq, apache maven e gradle

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate possesses exceptional, deeply technical skills in AI, LLMs, and systems automation, aligning with the core chatbot responsibilities. However, the complete lack of stated experience with the ServiceNow platform is a critical gap for a role advertised as a 'ServiceNow Architect', making it a poor fit despite the strong underlying technological expertise. **⚠️ Critical Gaps:** - ServiceNow platform experience **✅ Strengths:** - Deep, fundamental experience with LLMs and AI infrastructure. - Proven ability to architect complex, end-to-end automated systems. - Strong Python, API integration, and backend development skills. **❌ Missing Required:** ServiceNow, HTML, JavaScript, Bootstrap

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong conceptual fit for an SRE/Systems Architect role, with proven experience in automation (Terraform, CI/CD), containerization (Docker), and building resilient production systems from scratch. However, there is a critical gap as they lack any experience with Datadog, which is a core requirement for being a technical reference in the role. **⚠️ Critical Gaps:** - Datadog **✅ Strengths:** - Deep experience in automation (Python, Terraform, CI/CD) - Proven ability to architect and operate resilient, production-grade systems - Fast learner with a strong career trajectory towards complex systems engineering **❌ Missing Required:** Datadog, Hybrid/Multicloud experience (Azure, On-Premises), Formal SLO/SLI implementation and tracking

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect with proven self-teaching abilities, particularly in AI and automation. However, there is a critical and disqualifying gap in the core technology stack; the role requires deep expertise in the Oracle ecosystem (OIC, ORDS, OCI) and Java/.NET, none of which are present in the candidate's experience, which is focused on Python and open-source tooling. **⚠️ Critical Gaps:** - The entire required technology stack is based on Oracle (OIC, ORDS, OCI), for which the candidate has no experience. - Required development languages are Java and .NET, whereas the candidate's expertise is in Python. **✅ Strengths:** - Proven Fast Learner with deep expertise in self-hosting complex systems (AI Clusters). - Strong background in Systems Architecture and designing automated, production-grade systems. - Experience with containers (Docker) and CI/CD principles. **❌ Missing Required:** Oracle Integration Cloud (OIC), Oracle REST Data Services (ORDS), Java, .NET, Modelagem e governança de APIs (Apigee, Kong, WSO2, etc.), Cloud: Oracle Cloud Infrastructure, Experiência com mensageria: Kafka, RabbitMQ, SQS, Service Bus

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] Candidate is disqualified due to a fundamental mismatch in domain expertise and qualifications. The role requires an Architect with deep experience in BIM software for the construction industry, while the candidate is a Systems Engineer specializing in AI infrastructure, software, and logistics. There is no overlap in core competencies, required degree, or tooling. **⚠️ Critical Gaps:** - Domain Mismatch: Candidate is in Software/AI, while the job is in Architecture/Construction. - Missing Mandatory Degree: The job requires 'Arquitetura e Urbanismo', but the candidate has 'Engenharia - Mecatrônica'. - Lacks all required BIM software experience (Revit, Navisworks, etc.). **✅ Strengths:** - Proven Fast Learner in complex technical domains - Strong systems architecture and automation skills - Deeply technical in software, data, and infrastructure **❌ Missing Required:** Graduação: Arquitetura e Urbanismo, Especialização: Pós-graduação ou MBA em Gestão de Projetos (PMI/PMP) ou Tecnologia BIM, Domínio de ferramentas BIM: Autodesk Revit, Navisworks, Softwares de colaboração (BIM 360, etc.)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong technologist with proven fast-learning capabilities and a clear career progression towards complex systems architecture. However, there is a critical and disqualifying gap: zero experience with the core Microsoft Dynamics 365 platform, which is a non-negotiable requirement for this senior consultant role. **⚠️ Critical Gaps:** - The entire job is focused on Microsoft Dynamics 365, a platform the candidate has no demonstrated experience with. **✅ Strengths:** - Proven fast learner with a strong technical foundation - Fluent in English (C2) - Deep experience in systems design, automation, and API integration **❌ Missing Required:** 7+ years of experience in Microsoft Dynamics 365 projects, Knowledge of Dynamics 365 CE modules, Experience with ALM for Microsoft environments

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a skilled Systems Architect in backend, AI, and data domains but has a critical gap with no experience in the required Adobe Experience Manager (AEM) platform or the broader marketing technology stack. The role requires an AEM subject matter expert, making this a fundamental mismatch. **⚠️ Critical Gaps:** - The candidate's entire professional experience is in backend/AI/data infrastructure, while the role is for a lead architect in the Adobe Experience Manager (MarTech/CMS) ecosystem. **✅ Strengths:** - Strong backend and systems architecture background - Proven ability to automate complex processes - Experience leading engineering projects **❌ Missing Required:** Adobe Experience Manager (AEM), Adobe Target, AEM Dispatcher, AEM architecture design

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a strong match due to demonstrated expertise in architecting complex, automated systems from the ground up (JIT inventory, AI clusters). His experience as a founder and systems engineer in a startup context aligns perfectly with the role's requirements. The career trajectory shows a clear and intentional progression towards this exact type of senior technical role, and the 'fast learner' evidence mitigates gaps in specific listed technologies. **✅ Strengths:** - Proven ability to design, build, and deploy complex production systems end-to-end. - Deep expertise in automation and systems integration (Python, APIs). - Career progression shows strong motivation and alignment with a Solutions Architect path. **❌ Missing Required:** Agile methodologies (Scrum, Kanban), Experience with multiple cloud platforms (Azure, GCP), NoSQL database experience

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit due to a critical domain gap; they have no experience in the required Telco OSS/BSS sector. Furthermore, they fail to meet the 20+ years of experience requirement and lack key technologies like Java/J2EE. While a proven fast learner with transferable architecture skills, the specific knowledge required is absent. **⚠️ Critical Gaps:** - Lack of any experience in the Telecommunications (Telco) domain - Experience is in E-commerce/Finance/AI, not OSS/BSS platforms **✅ Strengths:** - Proven fast learner with track record of mastering new domains - Strong systems architecture and automation skills - Deep experience with Python and data-driven systems **❌ Missing Required:** 20+ years of experience (candidate has ~12), 10+ years in Telco architecture leadership, Java/J2EE, OSS/BSS integration experience, Experience with Telco operators (Tier 1/2)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect with deep expertise in software, AI, and data-driven logistics automation. However, this is a fundamental domain mismatch, as the role requires a background in civil/architectural engineering for the design and construction of physical facilities. The candidate's experience is in the digital realm, not the physical one. **⚠️ Critical Gaps:** - Candidate's background is in software/AI systems architecture, whereas the role requires expertise in civil/architectural design for physical logistics facilities. **✅ Strengths:** - Conceptual understanding of logistics and supply chain from a systems/data perspective - Proven fast learner with a strong technical aptitude - Experience with cross-functional processes in a technology context **❌ Missing Required:** Autocad, Atuação com projetos arquitetônicos e/ou civis, Experiência com compatibilização de disciplinas técnicas, Atuação comprovada com fornecedores de projeto executivo e apoio a obras

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate vastly exceeds the requirements for a Junior Data Architect role, demonstrating advanced, hands-on experience in designing and building complex data systems like self-hosted AI clusters. His proven fast-learning ability, extensive Python skills, and relevant financial market background make him an exceptionally strong fit. The candidate is overqualified, indicating high potential for rapid growth. **✅ Strengths:** - Advanced Systems Architecture (AI Clusters, JIT systems) - Proven Fast Learner & Self-starter - Extensive Python & Automation Expertise

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a strong architectural fit, with proven experience designing complex, automated systems from the ground up. While they lack direct experience in the specific Node.js stack, their demonstrated ability as a fast learner in deep technical domains (like self-hosting LLM clusters) and their strong foundation in Python, SQL, and system design make them an excellent candidate to architect the framework's backbone. The lack of frontend experience is not a critical gap for this architecture-focused role. **✅ Strengths:** - Proven experience in greenfield system architecture - Deep understanding of automation and integration - Strong 'Fast Learner' profile with a track record of mastering new domains **❌ Missing Required:** Node.js (TypeScript), Fastify, Apollo, Redis

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is an exceptionally strong match for multiple strategic roles, including AI/ML Engineer, DevOps/SRE, and Software Architect. Their resume demonstrates a rare and valuable combination of hands-on AI infrastructure experience (self-hosted LLMs), complex systems architecture (automated JIT system), and a proven track record in Python. The career trajectory shows a deliberate and successful progression from business domains to deep technical leadership. **✅ Strengths:** - Hands-on AI/LLM Infrastructure Experience - Complex Automated Systems Architecture (demonstrated) - Strong, recent Python expertise in production

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong technical architect with proven experience in automation, systems design, and data-driven projects, aligning with several core requirements. However, there is a critical gap in the required deep domain expertise in transportation and logistics, which is the absolute core of this principal-level role. **⚠️ Critical Gaps:** - The role is for a Principal Architect in Transportation Strategy, but the candidate's domain expertise is in AI Infrastructure and Systems Architecture, not transportation or logistics. **✅ Strengths:** - Strong experience in systems architecture and building automated, data-driven systems from scratch. - Proven fast learner with a track record of mastering new, complex technical domains (Finance, AI). - Meets general requirements for project management, cross-functional work, and process automation. **❌ Missing Required:** Transportation domain expertise, Experience managing, analyzing and communicating results to senior leadership

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong match on the core AI, backend, and infrastructure requirements, with a proven history of building complex systems from scratch. The career trajectory and 'fast learner' profile align perfectly with the needs of an early-stage venture. The only significant gap is the lack of demonstrated frontend experience, which is a risk for a full-stack MVP role but is mitigated by the candidate's proven ability to self-teach complex domains. **⚠️ Critical Gaps:** - Frontend development (React / Next.js) **✅ Strengths:** - Deep AI infrastructure experience (self-hosted LLMs) - Proven ability to build complex systems from scratch (trading bots) - Ideal career trajectory moving towards AI leadership **❌ Missing Required:** React / Next.js

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong technical architect with deep, hands-on experience building complex, scalable systems that directly map to the core responsibilities. Their career shows a clear progression of translating business needs into production infrastructure. The profile is only weakened by a lack of stated experience with the specific formal enterprise frameworks (TOGAF) and modeling notations (UML/BPMN) requested. **✅ Strengths:** - Architecting and building production-grade systems from scratch (JIT, AI Clusters) - Deep experience translating complex business domains (Finance, Supply Chain) into technical solutions - Strong foundation in modern infrastructure (Docker, CI/CD, AWS) **❌ Missing Required:** TOGAF, UML/BPMN tools

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate is a strong Systems Architect and Python developer with proven leadership and a talent for self-teaching complex domains like AI infrastructure. However, there is a major gap in the required Azure-specific technologies and Big Data frameworks (Spark/Hadoop), making this a high-potential but currently weak match for a role centered on the Azure ecosystem. **✅ Strengths:** - Deep Python and Automation Skills - Proven Systems Architecture (from scratch) - Strong AI Infrastructure Experience (On-Prem) **❌ Missing Required:** Microsoft Azure Platform Experience, Big Data Technologies (Hadoop, Spark, Hive), Formal Data Modeling (Star Schema, Snowflake)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate is a strong systems architect with proven Python and Terraform skills but has a critical gap in the required deep Azure and AWS cloud-native experience. Their career shows a strong learning trajectory, but they lack the specific hands-on expertise in the specified cloud platforms and their IaC tools. **⚠️ Critical Gaps:** - Extensive (3+ years) experience in Azure and AWS environments **✅ Strengths:** - Strong Python proficiency with demonstrated application - Direct experience with Terraform - Proven fast learner with a strong technical trajectory **❌ Missing Required:** Advanced proficiency in ARM templates, Bicep, Azure Resource Manager, Advanced proficiency in AWS CloudFormation and AWS CDK

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong fit for the Technical Lead aspects, with proven experience in systems architecture, project ownership, and infrastructure design. His self-hosted AI projects infer deep Linux and datacenter skills, though he lacks the specific enterprise Oracle/Exadata hardware and deep multi-cloud expertise required. **✅ Strengths:** - Proven Systems Architecture (JIT System) - Hands-on AI/GPU Infrastructure Experience - Leadership as Founder/Head of Engineering **❌ Missing Required:** Exadata and other Oracle hardware, Multi-cloud expertise (OCI, Azure), Hyperconvergence, Oracle (Database)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong conceptual fit with proven experience in systems architecture and AI infrastructure from the ground up. The career trajectory shows a clear and successful progression toward this type of role. The primary gap is the lack of specific, deep experience with the GCP ecosystem, which is a core requirement. **✅ Strengths:** - Systems Architecture - AI Infrastructure (from scratch) - Production-grade Automation **❌ Missing Required:** Strong expertise with GCP services (Cloud Run, GKE, Pub/Sub, Cloud Functions, Cloud Storage, BigQuery, Vertex AI), Familiarity with Google Gemini APIs

[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