[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled technical architect and engineer with an impressive track record of building complex systems. However, this is a poor fit for a formal Project Manager (PMO) role, which requires experience with methodologies like PMBOK/Agile and tools like Jira, all of which are absent from the resume. The candidate's career is trending deeper into hands-on architecture, while this role is focused on process, budget, and stakeholder management. **⚠️ Critical Gaps:** - Project Management vs. Systems Architecture: Candidate's experience is in building systems, not in formal project management of system implementations. **✅ Strengths:** - Deep understanding of technical systems (ERP/WMS-adjacent) - Proven leadership of technical teams/projects - Strong problem-solving and automation mindset **❌ Missing Required:** Knowledge of PMBOK, Experience with Agile methodologies (Scrum, Kanban), Experience with project management tools (Jira, Trello, Microsoft Project, etc.), Familiarity with formal project management practices (Change Requests, lessons learned documentation)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates strong technical leadership and architecture skills in relevant domains like AI infrastructure and algorithmic trading, coupled with a proven fast-learner aptitude. However, the role requires deep experience with specific digital banking products (PIX, TED, etc.) and BACEN regulatory compliance, which are not directly evidenced in the resume. While possessing transferable skills, the lack of this core domain and regulatory expertise positions him as a weaker match for this specialized project leadership role. **✅ Strengths:** - Strong project leadership and technical delivery from entrepreneurial ventures and past financial roles. - Deep technical expertise in AI infrastructure, automation, and systems architecture. - Proven fast learner with a strong analytical and problem-solving mindset. **❌ Missing Required:** Specific banking products (PIX, TED, TEF, boletos, cards, open finance, CCB, NC, Core Banking), BACEN regulatory knowledge, Fintech compliance expertise

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong match with exceptional analytical and problem-solving skills, coupled with direct experience in financial systems and highly regulated environments. While lacking explicit operational JML and IT access management experience for a 'Junior' role, their proven 'fast learner' ability and architectural understanding of security controls indicate a rapid upskill potential. **✅ Strengths:** - Exceptional analytical and problem-solving skills, demonstrated through complex system architecture and automation. - Strong understanding of financial systems and a highly regulated environment, directly relevant to FinTech. - Proven ability to self-teach and adapt to new technologies rapidly, indicating high potential for mastering operational aspects of access management. **❌ Missing Required:** Specific operational experience with Joiners, Movers, Leavers (JML) processes., Direct experience as a first point of contact for user login support., Explicit experience in maintaining dedicated device inventory for critical platforms.

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate is a strong fit for a Senior IT Project Analyst role, demonstrating extensive experience in leading, architecting, and managing complex software development projects with a focus on automation and efficiency. Key strengths include project management, CI/CD, resource control, and a strong analytical background. The primary gaps are specific frontend technologies (Node.js, React). **✅ Strengths:** - Strong Project Leadership & Systems Architecture Experience - Proven ability to control costs, resources, and schedules in technical projects - Expertise in CI/CD, automation, and process implementation **❌ Missing Required:** Node.js, React

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates strong technical architecture, automation, and system implementation skills, including CI/CD. However, there are critical gaps in specific organizational design frameworks (Spotify Model, Team Topologies), agile methodologies (Scrum, Kanban), and portfolio management practices (Lean Portfolio, OKRs) which are central to this Operational Model role. **⚠️ Critical Gaps:** - Deep knowledge in Spotify Model for team design - Deep knowledge in Team Topologies for team design **✅ Strengths:** - Exceptional 'Fast Learner' with a clear career trajectory towards advanced technical and AI roles. - Strong capabilities in technical architecture and implementation of complex, production-grade automated systems. - Proven ability to bridge business objectives with technical solutions, demonstrating strong problem-solving and hands-on building experience. **❌ Missing Required:** Practical experience in Scrum, Kanban and agility scalability, Experience in Lean Portfolio, OKRs and mensuration of success of transformation

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong capabilities in AI/LLMs, systems architecture, and automation, coupled with a proven fast-learner trajectory. However, the complete lack of explicit Rust programming experience, which is a critical and foundational requirement for this 'Rust Engineer' role, severely impacts the match. **⚠️ Critical Gaps:** - 1–2+ years of professional Rust development experience - Solid software engineering experience in backend services, command-line tools, or systems programming using Rust **✅ Strengths:** - Extensive experience with AI/LLMs, building autonomous agents, and evaluating AI-generated content. - Proven track record of building complex, automated production systems and self-teaching new technical domains. - Excellent English communication skills (C2 Certified) and a Bachelor's in a closely related engineering field. **❌ Missing Required:** Strong understanding of Rust’s ownership, borrowing, and lifetime model, with the ability to reason clearly about aliasing and data races, Ability to evaluate safe, idiomatic Rust code, including appropriate use of traits, generics, pattern matching, and error handling

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong background in systems architecture, automation, and data-intensive project leadership, including CI/CD and cloud infrastructure. However, there are notable gaps in specific data governance, data quality monitoring, and expertise with common ETL/data processing frameworks like DBT and Apache Spark, which are crucial for a senior data engineering role. **⚠️ Critical Gaps:** - Data governance (RBAC, LGPD/GDPR) **✅ Strengths:** - System Architecture & Automation (CI/CD, Python) - Proven Track Record in Data-Intensive Projects (JIT, Trading Bots) - Fast Learner & Strong Technical Trajectory **❌ Missing Required:** Data quality monitoring, DBT, Apache Spark

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate presents strong architectural, automation, and CI/CD skills, backed by a significant fast-learner bonus. However, a critical gap exists in MongoDB administration, a primary requirement. While related skills infer some Kubernetes and cloud knowledge, explicit experience with GCP and solid Kubernetes proficiency is missing. **⚠️ Critical Gaps:** - Administração de MongoDB **✅ Strengths:** - Strong expertise in automation, CI/CD pipelines, and system architecture with Python and Terraform. - Proven ability to build and deploy complex, resilient production systems, including self-hosted AI infrastructure. - Exceptional fast-learning capability and a clear, intentional career progression into technical and infrastructure roles. **❌ Missing Required:** Administração de MongoDB, Kubernetes (sólida experiência), GCP (experiência)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate presents a strong background in general systems architecture, Python automation, and demonstrable experience in building production-grade systems, showcasing significant learning agility. However, there's a notable gap in specific AWS data management architectures and associated services like Databricks, Spark, AWS Glue, and other core Data Factory tools, which are critical for this role's stated requirements. **⚠️ Critical Gaps:** - Strong experience with various Data Management architectures, specifically in an AWS environment (candidate has general architecture, but AWS data-specific expertise is weak). **✅ Strengths:** - Strong Python and automation skills applied to real-world systems. - Proven ability to architect and deploy production-grade, self-sustaining technical solutions, including AI infrastructure. - Exceptional learning agility and a clear career progression towards technical and AI-focused roles. **❌ Missing Required:** Experiência com tecnologias de mensageria, Conhecimentos sólidos em Databricks, Conhecimentos sólidos em Spark, Conhecimentos sólidos em Scala, Conhecimentos sólidos em S3, Conhecimentos sólidos em AWS Glue, Conhecimentos sólidos em AWS Athena, Conhecimentos sólidos em AWS Lambda, Conhecimentos sólidos em AWS Step Functions, Experiência em EMR

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong background in data analysis, system architecture, and business acumen, highly relevant for a BI Intelligence role. While specific tools like Power BI and Pentaho are not explicitly mentioned, the candidate's experience in building automated JIT inventory systems, algorithmic trading bots, and custom automation pipelines demonstrates a solid understanding and practical application of underlying data processing and reporting concepts. The 'Fast Learner' bonus and relevant career trajectory further enhance the match. **✅ Strengths:** - Strong business acumen, strategic thinking, and problem-solving capabilities applied to data-driven systems (e.g., ROI-focused systems, JIT inventory). - Demonstrated proficiency in building and automating complex data pipelines and analytical solutions using Python and scripting. - Exceptional learning agility and adaptability, evidenced by self-taught AI infrastructure, algorithmic trading, and continuous education, enabling rapid acquisition of new tools. **❌ Missing Required:** Power BI (specific tool), Pentaho (specific tool)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates strong technical proficiency, particularly in system architecture, automation, and AI infrastructure, coupled with a valuable 'fast learner' aptitude and relevant transferable domain experience. However, there are significant gaps in direct experience with formal project management methodologies and, crucially, in leading and coaching other project managers, which are key requirements for a Senior Project Manager Engineering role. **✅ Strengths:** - Deep technical interest and 'builder' mindset in infrastructure and automation - Proven track record of designing and delivering complex, self-sustaining systems (JIT, AI clusters) - Strong transferable domain expertise (Supply Chain, Mechatronics) highly relevant to transport/engineering **❌ Missing Required:** Extensive direct project management experience (beyond technical project leadership), Proven experience acting as a role model, coaching, and leading peer Project Managers

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong technical architecture, automation, and AI infrastructure skills, along with a proven fast-learning ability and transferable domain experience in procurement and supply chain. However, the role is highly specialized, demanding extensive (5+ years) SAP MM implementation and support expertise, including specific modules like FI/CO integration, ECC lifecycle, SOLMAN, and Opentext VIM, none of which are substantially present in the candidate's recent profile. This fundamental mismatch in core technical stack constitutes a critical gap, making the candidate a poor fit for this specialized SAP MM role. **⚠️ Critical Gaps:** - Core SAP MM expertise for implementation, configuration, and support of procurement operations **✅ Strengths:** - Strong background in building and automating complex systems (JIT, AI infra) - Demonstrated fast learning ability and career progression towards technical/AI roles - Transferable domain knowledge in procurement and supply chain **❌ Missing Required:** SAP MM Implementation and Support (deep, 5+ years expertise), SAP ECC implementation phases knowledge, Solution Manager (SOLMAN) knowledge, SAP MM integration with FI/CO and Logistics, Opentext VIM experience, Argentina localization expertise, Basic Spanish proficiency

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate demonstrates a strong foundation in systems architecture, automation, and AI infrastructure, including direct experience with self-hosting LLMs, which aligns well with the job's technical demands. Their proactive career progression and self-taught capabilities earn a significant 'fast learner' bonus. However, the candidate lacks explicit experience with specific required data platforms (Databricks, PySpark, SQL) and several modern AI/GenAI frameworks (LangChain, TensorFlow, PyTorch, Hugging Face), resulting in deductions despite inferred underlying capabilities. **✅ Strengths:** - Robust experience in Systems Architecture, software engineering, and delivering production-grade automated solutions. - Demonstrated expertise in AI Infrastructure, including self-hosting and optimizing Large Language Models (LLMs). - Exceptional 'Fast Learner' profile and a clear, intentional career trajectory towards AI/technical leadership. **❌ Missing Required:** Databricks, SQL, PySpark, Agile Methodologies, LangChain, LangGraph, Agno, TensorFlow, PyTorch, Hugging Face

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates exceptional backend, infrastructure, and automation skills with a strong track record of end-to-end project ownership in startup-like environments. However, a significant gap exists in demonstrated 'strong modern frontend development' experience, which is a key requirement for this full-stack role, impacting the overall match. **⚠️ Critical Gaps:** - Strong experience with modern frontend development **✅ Strengths:** - Exceptional backend, infrastructure, and automation expertise - Proven end-to-end project ownership and startup experience - Strong problem-solving skills and fast learner with a relevant career trajectory

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate presents an exceptionally strong match, demonstrating extensive practical experience in building and optimizing complex AI/ML systems and strong transferable skills in finance and risk management. While Scala and specific knowledge of loss provisions modeling are missing, the depth of relevant experience and 'fast learner' trait heavily compensate, indicating a high potential for success in the Model Risk team. **✅ Strengths:** - Extensive practical experience building and optimizing complex ML/AI systems (LLMs, trading bots, JIT inventory), directly applicable to model review and enhancement. - Strong background in finance and risk management (algorithmic trading, financial analysis), providing critical domain context for credit models. - Proven 'fast learner' and systems architect, demonstrating autonomy, problem-solving, and adaptability to new technologies.

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate presents strong experience in systems architecture, AI infrastructure, and automation, demonstrating a proactive learning approach. However, the core requirement of extensive professional C++ development experience, particularly 7+ years in production for systems-level applications, is entirely absent from the resume, constituting a critical domain mismatch for a Senior C++ Engineer role. **⚠️ Critical Gaps:** - C++ Development (7+ years production experience) **✅ Strengths:** - AI infrastructure and LLM optimization - Systematic and methodical approach to complex systems - Strong automation and CI/CD experience

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong technical architect with proven project execution skills in an entrepreneurial setting, but critically lacks experience in the formal project management methodologies (Scrum, PMBOK) and the specific domain (Cyber Security) required for this coordination role. While he has a relevant educational background, his career trajectory towards deep-tech infrastructure makes him a questionable fit for a process-oriented position. **⚠️ Critical Gaps:** - Cyber Security / Cyber Risk domain expertise - Formal Agile/Traditional Project Management methodologies (Scrum, Kanban, PMBOK) **✅ Strengths:** - Strong technical and engineering background (matches education requirement) - Proven ability to deliver complex technical projects end-to-end - Fast learner with experience in high-pressure domains (finance, AI) **❌ Missing Required:** Experience with Scrum, Kanban, PMBOK, or PRINCE2, Experience in Cyber Security or Operational Resilience

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect with proven skills in AI infrastructure and automation. However, this is a critical domain mismatch. The role requires a deep background in Materials Science and Chemical Engineering, which the candidate does not possess. The candidate's experience is in software and systems, while the job is focused on physical materials (niobium), chemical processes, and laboratory R&D. **⚠️ Critical Gaps:** - Materials Science - Chemical Engineering - Laboratory R&D **✅ Strengths:** - Proven fast learner with track record of self-teaching complex domains - Strong systems architecture and automation skills - Fluent English **❌ Missing Required:** Familiarity with chemical/materials processing software, Knowledge of chemical and materials engineering processes, Advanced materials characterization techniques, Experience in new materials development, Experience with pilot-scale projects and laboratory testing

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong technical fit, with proven experience in building automated systems, managing data-driven processes, and working in adjacent financial markets (crypto). However, they lack direct experience in commodities, price reporting agencies (PRAs), and specific regulatory frameworks like IOSCO, which is a notable gap. **✅ Strengths:** - Extensive experience in process automation with Python - Proven ability to design and manage complex, data-reliant systems (JIT, Trading Bots) - Fast learner with a strong technical foundation in systems and data analytics **❌ Missing Required:** Direct experience with commodities markets and pricing, Knowledge of PRA regulatory frameworks (e.g., IOSCO)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect with a proven ability to learn and an excellent career trajectory toward data-centric roles. However, there is a critical gap, as they lack hands-on experience with the entire Modern Data Stack (Snowflake/Databricks, DBT, Airflow) and have only basic cloud knowledge, all of which are core requirements for this specific Staff Data Engineer position. **⚠️ Critical Gaps:** - No demonstrated experience with the required Modern Data Stack platforms (Snowflake, Databricks, BigQuery, DBT, Airflow), which are central to the role's responsibilities. **✅ Strengths:** - Systems Architecture & End-to-End System Design - Proven Fast Learner with hands-on AI infrastructure experience - Strong problem-solving and business-to-technical translation **❌ Missing Required:** 5-8+ years in a titled Data Engineering/Architecture role, Solid experience with a major cloud ecosystem (AWS, GCP, or Azure), Experience with Snowflake, Databricks, or BigQuery, Experience with DBT, Experience with orchestration tools like Airflow, Prefect, or Dagster

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled technologist and systems architect, but this role is for an ERP Project Manager. There is a significant mismatch between the candidate's recent career trajectory towards AI/Infrastructure and the job's focus on business process management. While he possesses foundational ERP-related experience and strong project leadership skills, the lack of recent, direct ERP implementation management experience is a major gap. **⚠️ Critical Gaps:** - Career trajectory mismatch (deep tech/AI vs. ERP Project Management) - CNH B e veículo próprio (unverified hard requirement) **✅ Strengths:** - Deep understanding of business rules (Supply Chain, Finance) - Proven leadership in complex technical projects (Founder role) - Fluent in English, meeting a 'nice-to-have' criterion **❌ Missing Required:** Experiência com gerenciamento de projetos de implantação de ERP, CNH B e veículo próprio

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is an accomplished Systems Architect with impressive, relevant experience in AI infrastructure, automation, and systems thinking. However, the role is for a specialist Senior C Engineer, and the candidate's resume demonstrates no experience in C development, which is the primary, non-negotiable requirement of the job. **⚠️ Critical Gaps:** - The role requires expert-level, hands-on C programming for production software and code review, while the candidate's entire professional experience is in higher-level systems architecture using Python and shell scripting. **✅ Strengths:** - Deep expertise in AI infrastructure and systems architecture. - Proven 'Fast Learner' with a strong track record of self-teaching complex domains. - Directly relevant domain experience in training and deploying AI systems. **❌ Missing Required:** 4+ years of professional experience developing production software in C, Expert-level proficiency in C (pointers, memory management, undefined behavior), Hands-on experience with C build systems, compilers, and debuggers, Proven experience conducting detailed code reviews in C

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect and automator with proven experience in Terraform and Python scripting. However, there are critical gaps in the required core technologies, specifically a lack of deep, production-level experience in AWS and Kubernetes, which are central to the SRE role described. His 'metal-up' background contrasts with the cloud-native focus of the job. **⚠️ Critical Gaps:** - Forte domínio de AWS (candidate has on-prem focus and only basic AWS knowledge, which is a domain gap for a cloud-native role) - Conhecimento aprofundado em Kubernetes (candidate has experience with local AI clusters, but no demonstrated K8s experience) **✅ Strengths:** - Infrastructure as Code (Terraform) - Automation Scripting (Python, Shell) - Complex On-Premise System Architecture (JIT Inventory, AI Clusters) **❌ Missing Required:** Experiência sólida com AWS (EC2, EKS, RDS, S3, VPC, IAM e Route53), Conhecimento aprofundado em Kubernetes e seus principais componentes, Experiência com ArgoCD e conceitos de GitOps

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] This is a POOR_FIT. The candidate is a talented hands-on Systems Architect and AI Engineer, but lacks the fundamental requirements for this role. The position is for a senior executive Program Director with deep experience in SAP S/4HANA implementations within the Utilities sector, none of which are present in the candidate's resume. His career trajectory is moving towards deep-tech infrastructure, not executive-level enterprise software consulting. **⚠️ Critical Gaps:** - The candidate has zero experience with SAP, while the role is centered entirely on leading SAP S/4HANA projects. - The role requires deep domain knowledge of the Utilities/Energy sector, which is completely absent from the candidate's background. **✅ Strengths:** - Proven ability to learn complex technical domains quickly ('Fast Learner' bonus applied). - Strong background in systems architecture and automation. - Experience in supply chain, which is tangentially related to large-scale operations. **❌ Missing Required:** Experiência comprovada em gestão de programas/projetos SAP, Histórico comprovado em implementações SAP S/4HANA, Vivência no segmento Utilities / Energia e domínio de CCS, Forte atuação em consultorias multinacionais

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a highly capable systems architect and engineer with a proven track record of delivering complex technical projects from scratch. However, the role requires a Delivery Manager with extensive experience in corporate, multi-stakeholder environments and formal agile processes, which is a significant gap in the candidate's background. His strengths are in deep technical execution and systems building, not the cross-functional orchestration and executive communication required for this position. **⚠️ Critical Gaps:** - Lacks experience in a formal Project/Delivery Management role within a large, multi-stakeholder corporate environment. **✅ Strengths:** - Proven ability to architect and deliver complex, automated systems from concept to production. - Deep understanding of business domains like Supply Chain and Finance, providing strong business acumen. - Exceptional problem-solver and documented fast learner across different technical domains (AI, Quant, Cloud). **❌ Missing Required:** Experiência sólida como Gerente de Projetos / Delivery Manager, Vivência em ambientes multidisciplinares, com múltiplos stakeholders, Excelente comunicação executiva, verbal e escrita, Experiência com ferramentas como Jira, Confluence e Miro

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and a proven fast learner with excellent Python and general infrastructure skills. However, there is a critical gap between their on-premise/generalist experience and the job's specific requirements for the AWS data ecosystem (Glue, Redshift, Kinesis, PySpark), making it a poor fit for a role that requires immediate, specialized platform knowledge. **⚠️ Critical Gaps:** - Deep experience with the required AWS data stack (Glue, Kinesis, Redshift, etc.) - Experience with large-scale data processing using PySpark, Databricks, or EMR **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex systems (AI, Algo-trading) - Strong Python skills for automation, data analysis, and backend logic - Experience designing and deploying production-grade automated systems from scratch **❌ Missing Required:** AWS Glue, kinesis, Redshift, Athena, Aurora, PySpark, Databricks, EMR, Data lakes, Data mesh

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit due to a fundamental mismatch in domain and required tooling. The role requires expertise in architectural/product design and budgeting using AutoCAD and SketchUP, whereas the candidate is a highly technical Systems/AI Infrastructure Architect with a background in software, data, and process automation. His career trajectory is moving towards deep technology, which is divergent from the corporate design focus of this role. **⚠️ Critical Gaps:** - The job requires architectural and product design skills (AutoCAD, SketchUP) for corporate projects, while the candidate's expertise is in software/infrastructure architecture (Python, Docker, AI Clusters). **✅ Strengths:** - Forte capacidade analítica e de resolução de problemas em sistemas - Experiência com planejamento financeiro, de produção e compras - Histórico comprovado como autodidata rápido em domínios técnicos complexos **❌ Missing Required:** AutoCAD, SketchUP, Experiência prévia na área de projetos e orçamento no mercado corporativo (design)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect and proven fast learner with leadership qualities, but critically lacks hands-on experience with the required enterprise integration, streaming, and API gateway platforms (e.g., Mulesoft, Kafka, Apigee). His impressive experience is in custom-coded integrations (Python/automation), representing a fundamental mismatch with the platform-centric expertise explicitly requested. **⚠️ Critical Gaps:** - Experiência com ferramentas de integração (Mulesoft, Oracle SOA, NiFi, Boomi, Apache Camel, etc.) **✅ Strengths:** - Systems Architecture & Automation - Proven Fast Learner & Self-Taught in Complex Tech (AI/Quant) - CI/CD Pipeline Experience **❌ Missing Required:** Experiência com soluções de streaming e mensageria (Kafka, Solace, Pulsar, RabbitMQ, etc.), Experiência em API Gateway e Gerenciamento de APIs (Apigee, Kong, Gravitee, etc.)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled systems architect with a proven track record of designing and building complex, automated systems from the ground up. However, the role is focused on formal project and people management within a corporate structure, which represents a critical gap in the candidate's demonstrated experience. His career is trending towards deep technical architecture, while this role requires team leadership and stakeholder management. **⚠️ Critical Gaps:** - People Management (Gestão de Pessoas) - Formal Team Leadership **✅ Strengths:** - Deep experience in process automation and systems design - Proven ability to self-teach and master complex technical domains - Strong background in finance and supply chain analytics **❌ Missing Required:** Formal project management in a corporate setting, Experience managing project teams/squads, Building formal business cases

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] O candidato é um arquiteto de sistemas e líder técnico, mas a vaga é para um Gerente de Projetos formal. Há uma lacuna crítica na experiência com metodologias ágeis (Scrum/Kanban), gestão financeira de projetos e ferramentas como Jira. Embora demonstre liderança e capacidade de tradução entre negócios e tecnologia, falta-lhe a experiência central em gerenciamento de processos exigida. **⚠️ Critical Gaps:** - Experiência em Arquitetura de Sistemas/Engenharia versus a necessidade de Gestão de Projetos formal. **✅ Strengths:** - Liderança técnica e de negócios comprovada como fundador - Habilidade de atuar como 'ponte' entre áreas técnicas e de negócios - Forte histórico de aprendizado autodidata e aplicação de novas tecnologias **❌ Missing Required:** Domínio de metodologias ágeis (Scrum e Kanban), Experiência com gestão financeira de projetos (orçamento, forecast), Experiência com ferramentas Jira e Confluence, Experiência com métricas de desempenho ágil (Lead Time, Cycle Time)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong capabilities in system architecture, automation, and AI infrastructure, along with excellent general technical and language skills. However, there is a critical and fundamental gap in core frontend development experience, specifically lacking proficiency in HTML, CSS, JavaScript, TypeScript, and React, which are essential requirements for this Frontend Engineer role. **⚠️ Critical Gaps:** - Core frontend development experience (3+ years) - Proficiency in HTML, CSS, JavaScript, TypeScript, and React expertise **✅ Strengths:** - Deep expertise in system architecture and automation for complex backend systems. - Proven 'Fast Learner' ability to acquire and apply new technical skills rapidly. - Strong foundation in general software engineering practices, APIs, and robust authentication mechanisms (SSO/SAML). **❌ Missing Required:** Front-end testing frameworks (Jest, Cypress)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates exceptional technical acumen and extensive experience in AI infrastructure, e-commerce automation, and quantitative development. However, the core requirements of this 'Analista de Projetos - Designer Educacional' role, which demand specific experience in educational project management, instructional design, and pedagogical practices, are not met. The candidate's career trajectory and domain expertise are fundamentally misaligned with the job's focus. **⚠️ Critical Gaps:** - Required experience (2-3 years in educational project management/corporate education) is in a completely different domain (AI Infrastructure/E-commerce/Finance) without direct transferable application. - Required education (Pedagogy, Communication, Administration, Project Management related to educational content) is not met by a technical Engineering degree, leading to a significant domain knowledge gap. **✅ Strengths:** - Proven fast learner with a strong self-teaching track record in highly complex technical domains. - Extensive 10+ years of experience in system architecture, operations, and automation. - Strong analytical and problem-solving capabilities demonstrated across various technical and financial projects. **❌ Missing Required:** Experiência em gestão de projetos educacionais/educação corporativa, Superior completo em Pedagogia, Comunicação, Administração, Gestão de Projetos ou áreas correlatas (para atuação em projetos educacionais), Vivência na organização de sessões presenciais, híbridas ou remotas (com foco em eventos educacionais), Experiência na criação de materiais educacionais e multimídia, Noções de indicadores como NPS, CSAT, engajamento e presença (para avaliação de programas educacionais)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate demonstrates exceptional systems architecture, infrastructure experience (Docker, AWS, local AI clusters), and a strong ownership mentality, highly aligning with the role's core requirements. While direct experience with Rust, Go, or C++ is absent, the candidate's proven fast-learner ability and diverse technical background suggest strong adaptability to new systems languages, as valued by the job description. **✅ Strengths:** - Exceptional systems architecture and ownership, demonstrated by building and deploying complex, automated, production-grade systems (JIT inventory, LLM clusters). - Strong foundational and practical experience in infrastructure, cloud (Docker, AWS), and security/identity (SSO, RBAC), directly relevant to the role's focus on Edge software in the identity space. - Proven 'fast learner' with a clear career trajectory into advanced technical and AI infrastructure roles, indicating high adaptability to learn new technologies like Rust, as explicitly valued by the employer. **❌ Missing Required:** Excellent skills in systems languages such as Rust, Go, or C++ (specific languages)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong match for an Infrastructure & Operations role, demonstrating extensive experience in production environments, system automation, and critical system management. While showing foundational AWS knowledge and significant cloud/datacenter experience, the explicit 'solid knowledge in Cloud AWS' is a clear gap, preventing a perfect match. The candidate's self-taught approach and career trajectory are highly valuable assets. **✅ Strengths:** - Extensive experience in production environment operations, support, and sustenance, especially with automated systems and AI infrastructure. - Strong capabilities in automation, scripting (Python, Shell Script, Terraform) and CI/CD, demonstrating a proactive approach to operational efficiency. - Proven track record as a fast learner and builder, with a relevant career trajectory towards technical and AI infrastructure roles, coupled with experience in critical financial systems. **❌ Missing Required:** Conhecimentos sólidos em Cloud AWS

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate possesses strong foundational skills in infrastructure, automation, and system design, including some AWS experience and Terraform. However, the job's explicit requirements for proven experience in Azure, OCI, Datadog, AKS, and Oracle Database are critical gaps or missing required skills, making the candidate a poor fit despite a strong learning trajectory. **⚠️ Critical Gaps:** - Azure (Proven experience) - OCI (Proven experience) **✅ Strengths:** - Strong foundation in infrastructure, automation, and system design (Terraform, Docker, CI/CD, Python scripting). - Demonstrated ability to build and operate complex, automated systems (JIT inventory, self-hosted LLM clusters). - Proven 'Fast Learner' with a career trajectory aligned with technical/AI roles, indicating high adaptability. **❌ Missing Required:** Datadog, AKS, Oracle (Banco)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong technical abilities in automation (Python, Shell), cloud basics (AWS), and practical application of SRE principles through building and operating complex systems. However, there is a critical mismatch with the core functions of this IT Infrastructure Analyst role, which primarily focuses on first-line user support, incident response, ticket management, knowledge base maintenance, and training for L2 staff. The candidate's extensive architectural and engineering background is not directly aligned with these operational support responsibilities. **⚠️ Critical Gaps:** - Direct experience as a first-line IT support/incident response contact, handling user-reported issues and managing tickets for a diverse user base in a formal corporate IT environment. **✅ Strengths:** - Strong technical foundation in automation (Python, Shell) and cloud basics (AWS). - Proven ability to learn and implement complex technologies independently (Fast Learner bonus, AI infrastructure). - Extensive experience in architecting and operating resilient systems, demonstrating a deep understanding of system reliability. **❌ Missing Required:** Experience with IT ticket management systems (e.g., ServiceNow, Jira, GLPI), Experience with specific IT monitoring and observability tools (e.g., Zabbix, Grafana), Experience maintaining IT support knowledge bases and documenting IT support procedures, Experience training L2 IT support staff, Direct experience as a primary point of contact for user IT issues (calls/emails)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate is a highly skilled technical architect and engineer with strong English communication, but their experience is fundamentally misaligned with a formal Project Manager role. A critical gap exists in core project management experience, Agile methodologies, and proficiency with relevant tools like JIRA, making them a poor fit for this position. **⚠️ Critical Gaps:** - Lack of formal Project Management domain experience; candidate's primary background is in technical architecture and engineering. **✅ Strengths:** - Advanced English communication (C2 Certified/Fluent) - Proven Fast Learner with extensive self-taught technical capabilities and continuous education - Strong background in technical architecture, AI infrastructure, and systems engineering with a focus on ROI and automation **❌ Missing Required:** Experience as Project Manager, leading teams and managing projects (in a formal PM capacity), Experience with project management utilizing Agile Methodologies, Proficiency in JIRA or other task management tools (for task assignment, analysis, and reporting), Ability to manage multidisciplinary teams (UX/UI, QA, development, etc.) in a Project Manager role

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate demonstrates exceptional alignment with the job's core requirements, showcasing deep expertise in automation, AI/ML, and LLM solutions. Their proven career progression towards technical and AI roles, coupled with strong fast-learner evidence, makes them an outstanding match for this position, despite minor gaps in some preferred technologies. **✅ Strengths:** - Extensive experience in automation and AI-driven workflows, including direct LLM implementation and autonomous agents. - Proven Python expertise applied to complex systems like JIT inventory and algorithmic trading with a focus on operational efficiency. - Strong foundational knowledge in system architecture, cloud basics (AWS), CI/CD pipelines, and problem-solving through practical application.

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong technical and architectural background with significant experience in leading innovative projects, demonstrated through self-built systems and AI infrastructure. However, there's a notable gap in direct experience with corporate innovation project management, specifically concerning regulatory bodies like ANEEL and engagement with public research entities, which are key differentiators for this 'Pleno' role. **✅ Strengths:** - Exceptional technical depth and experience in building and leading highly innovative systems and AI infrastructure. - Proven fast learner with a strong, intentional career trajectory towards advanced technical and AI roles. - Strong project execution, analytical, and problem-solving capabilities demonstrated across diverse and complex projects. **❌ Missing Required:** Experiência prévia em gestão de projetos de inovação (contextual nuance for a 'Pleno' role in a large utility company), Pacote Office avançado

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong architectural, automation, and AI infrastructure skills with a clear business acumen. However, there are significant gaps in core data engineering platforms, including big data processing frameworks, specific cloud data services for analytics, advanced SQL, and multi-model database experience, which are critical for this role. The fast learner bonus and transferable skills mitigate the score but don't bridge the fundamental domain difference. **⚠️ Critical Gaps:** - Strong domain in big data and distributed processing (Spark, Hadoop, Flink) - Experience in hybrid and multi-model database architectures (relational and non-relational specific examples) **✅ Strengths:** - Strong architectural and system design capabilities with complex project delivery (JIT system, LLM clusters). - Proficiency in Python, automation, and CI/CD practices for system development and deployment. - Exceptional business acumen, ability to translate business needs into technical solutions, and focus on ROI and quantifiable metrics. **❌ Missing Required:** Solid experience in large-scale data engineering (traditional ETL/DW focus), Proficiency in analytical data architecture and modeling (Data Lake, Data Warehouse, Lakehouse), Advanced knowledge in SQL and complex query optimization, Specific Cloud Data Services for analytics (EKS, EMR, Lambda, S3, Redshift on AWS; BigQuery, DataFlow, Composer on GCP), ETL/ELT tools (dbt, Glue, Dataflow) and specific orchestration tools (Airflow, Step Functions, Prefect), Knowledge in data governance, security, and compliance specific to critical data environments

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate is a strong systems architect and automation engineer, directly matching the need to design and optimize operational infrastructure for Go-To-Market. While excelling in engineering and data-driven automation, the candidate lacks direct operational experience in RevOps/GTM strategy and specific CRM/prospecting tools. **✅ Strengths:** - Exceptional expertise in designing and implementing automated operational infrastructure and systems. - Strong track record in applying engineering principles to solve business problems, demonstrating high efficiency and scale. - Proven fast learner with a clear career trajectory towards advanced technical and AI-related roles. **❌ Missing Required:** Experiência em áreas de RevOps, GTM ou Growth B2B (specifically strategic/operational aspects), Conhecimento extenso das principais ferramentas de CRM, prospecção e data enrichment do mercado

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong architectural and automation skills in a traditional infrastructure and Python environment, but lacks direct experience or adjacent technologies within the Microsoft Power Platform ecosystem, C#, and Javascript, which are core requirements for this role. While a fast learner with transferable automation concepts, the fundamental domain and technology mismatch results in a low score. **⚠️ Critical Gaps:** - Microsoft Power Platform Ecosystem (including Power Apps, Power Automate, Copilot Studio, Dataverse, Dynamics 365) **✅ Strengths:** - Strong automation and system integration experience - Proven fast learner and self-starter, adaptable to new technologies - Extensive experience in building production-grade systems from concept to execution **❌ Missing Required:** C#, Javascript

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate presents a strong background in automation, Python, and system architecture, with a clear career progression towards AI and technical roles. However, there are significant gaps in specific programming languages (PowerShell, JavaScript, Go), certain cloud platforms (Azure, GCP), and NoSQL databases. Crucially, the hybrid work requirement in Morumbi/SP presents a geographic critical gap for a candidate only identified as 'Based in Brazil'. **⚠️ Critical Gaps:** - Geographic restriction: Hybrid role (2x week) in Morumbi/SP required, candidate 'Based in Brazil' without specified proximity or relocation willingness. **✅ Strengths:** - Exceptional Python and automation expertise demonstrated in complex, large-scale systems (JIT inventory, AI clusters). - Strong career trajectory and 'fast learner' ability, showing continuous acquisition of advanced technical skills relevant to systems architecture and AI. - Proven experience in system architecture, integration (APIs), and understanding of business logic across diverse domains (e-commerce, finance, supply chain). **❌ Missing Required:** PowerShell, JavaScript, Go, Azure, GCP, NoSQL

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates strong technical abilities in automation, system architecture, and software development, underpinned by a clear 'fast learner' trajectory. However, the resume lacks explicit and mandatory experience in core Quality Engineering areas such as functional testing, specific test automation frameworks like Cypress, and Agile methodologies. While possessing strong foundational engineering skills, the specific QA focus required for this role is not a direct match. **✅ Strengths:** - Robust background in automation, system architecture, and complex project delivery. - Exceptional 'fast learner' aptitude, demonstrated by self-taught advanced technical domains. - Proficiency in Python and practical experience with CI/CD concepts and API integration. **❌ Missing Required:** Experiência com Testes Funcionais, Experiência com framework de automação de testes Cypress, Experiência com Metodologias ágeis (Scrum, Kanban), Experiência com API (Postman)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a senior-level Systems Architect specializing in AI and automation, while the job is for a junior, manual-labor role as a Production Assistant on a factory floor. There is a complete and fundamental mismatch in skills, experience, and career trajectory. The candidate is critically overqualified and in an entirely different professional domain. **⚠️ Critical Gaps:** - The candidate's expertise is in high-level software/AI architecture, while the job requires manual, physical factory labor. This is a different career domain. **✅ Strengths:** - The candidate is not a fit for this role in any capacity. **❌ Missing Required:** Experience with factory operational routines, Material handling and separation, Supplying production lines

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate possesses exceptional and rare expertise in core AI infrastructure, evidenced by self-hosting LLM clusters. However, this is an AI *Infrastructure* profile, whereas the job is for a *Full-Stack AI Software Engineer*. The complete absence of the required core development stack (NodeJS, JavaScript/TypeScript, ReactJS, NextJS) represents a critical and disqualifying gap. **⚠️ Critical Gaps:** - NodeJS - ReactJS - NextJS - JavaScript/TypeScript **✅ Strengths:** - Deep practical experience with LLM infrastructure (self-hosted) - Proven ability to architect and build complex automated systems from scratch - Strong skills in Python for automation and data analysis **❌ Missing Required:** NodeJS, ReactJS, JavaScript / TypeScript, Testes automatizados (BDD)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is a skilled Systems Architect/AI Engineer with deep expertise in Python, automation, and infrastructure. However, this role is for a Senior Salesforce and Java Developer. There is a critical and fundamental gap between the candidate's Python-centric background and the required Java/Salesforce technology stack. **⚠️ Critical Gaps:** - The role requires senior-level Java and Salesforce development, but the candidate's entire development experience is in Python and Shell Scripting. **✅ Strengths:** - Strong experience in infrastructure and automation (Docker, Terraform, CI/CD) - Proven ability to architect and build complex systems from scratch (JIT inventory, AI clusters) - Demonstrated fast learner with a clear career progression towards technical depth **❌ Missing Required:** Java, Salesforce, Spring Boot, OmniStudio

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is severely overqualified in irrelevant technical domains (AI, Systems Architecture) and lacks the fundamental experience in accounts payable required for this transactional finance role. His career trajectory shows a clear and intentional move away from finance toward deep technology, making him a poor fit for this junior administrative position. **⚠️ Critical Gaps:** - Domain Mismatch: Candidate is a Senior AI/Systems Architect, while the job is a junior-level Accounts Payable clerk. - Career Trajectory Mismatch: Candidate's career is progressing rapidly into high-tech engineering, which is the opposite direction of this administrative finance role. - Education Mismatch: Job requires a degree in Finance or Administration; candidate's degree is in Mechatronics Engineering. **✅ Strengths:** - Portuguese fluency - Experience in finance-adjacent roles (though more than 7 years ago) - Proven ability to learn complex systems (though not in a relevant domain) **❌ Missing Required:** Experiência em departamento de contas á pagar (Experience in an accounts payable department)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] Candidate is DISQUALIFIED due to hard constraints (language and time zone). Beyond that, this is a POOR_FIT; the role requires a hands-on Backend Developer in the Node.js/TypeScript/MongoDB stack, whereas the candidate is a Python-focused Systems Architect. The core technical skills are a complete mismatch. **⚠️ Critical Gaps:** - The role is for a backend developer using TypeScript/Node.js/NestJS; the candidate's primary language is Python. - Required experience with NoSQL (MongoDB) and message queues (RabbitMQ) is completely absent. - The required language 'Russian' is not listed in the candidate's skills. - The candidate's location (Brazil, GMT-3) does not align with the required time zones (GMT+2 to GMT+5). **✅ Strengths:** - Excellent high-level systems architecture design - Proven ability to automate complex business logic (JIT inventory system) - Strong infrastructure experience (Docker, AI Clusters, CI/CD) **❌ Missing Required:** TypeScript/JavaScript, Node.js, NestJS, MongoDB, RabbitMQ, Russian

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] This is a poor match. The candidate is a highly technical Systems and AI Infrastructure Architect with a background in supply chain and algorithmic trading. The job is for a Senior Tax Analyst focused exclusively on Brazilian indirect taxes and fiscal compliance. There is a critical domain gap between the candidate's demonstrated skills in engineering/automation and the role's requirements for deep, specialized knowledge in accounting and tax law. **⚠️ Critical Gaps:** - The candidate is a Systems/AI Architect, while the role is for a Senior Tax Analyst. The domains are fundamentally different, requiring entirely separate knowledge bases and skill sets. **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex domains. - Fluent (C2) English, exceeding the intermediate requirement. - Strong problem-solving and system-building mindset. **❌ Missing Required:** Sólida experiência com tributos indiretos (ICMS, IPI, ISS, etc.), Domínio de obrigações acessórias (SPED, Bloco K, etc.), Conhecimento em operações de importação e benefícios fiscais (CFOPs), Experiencia em classificação de NCM e EX-Tarifario, Graduação em Contabilidade, Administração, Economia ou áreas correlatas