[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect with proven expertise in infrastructure-as-code (Terraform, Docker), CI/CD, and building complex automated systems. However, this is a Software Engineer role with a stack centered on Kotlin, Java, and Node.js, for which the candidate has no demonstrated experience, representing a critical skill gap. While they are a fast learner, the lack of foundational language proficiency makes this a poor fit. **⚠️ Critical Gaps:** - Proficiency in Kotlin, Java, and Node **✅ Strengths:** - Infrastructure & Cloud (Docker, Terraform) - CI/CD Pipeline Knowledge - Systems Architecture & Automation **❌ Missing Required:** Kotlin, Java, Node, Kafka, Ferramentas de observabilidade (Grafana, Kibana, Prometheus, Datadog)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and proven leader with deep experience in Python and building automated, resilient systems. However, there is a critical gap in the required web application stack (Next.js, Node.js), making them a poor fit for a role centered on web architecture leadership. **⚠️ Critical Gaps:** - Web Application Development (Next.js) **✅ Strengths:** - Systems Architecture - Team Leadership (Founder) - Python for Automation **❌ Missing Required:** Node.js, Proven experience in web application development

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect with excellent skills in Python, infrastructure, and automation, plus relevant domain experience in FinTech. However, this is a Java Application Support role, and the candidate has no demonstrated experience with the Java/J2EE ecosystem, which constitutes a critical and disqualifying gap for this specific position. **⚠️ Critical Gaps:** - Java/J2EE Application Support **✅ Strengths:** - Deep experience in FinTech and financial systems - Strong infrastructure, automation, and CI/CD background - Proven fast learner with a track record of self-teaching complex technologies **❌ Missing Required:** 4+ Years of Java/J2EE application support experience, CI/CD tools (Jenkins), Experience on Linux platform (explicit)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with advanced Python skills and a proven ability to build complex, automated data-driven systems from scratch. However, they lack direct, hands-on experience with the specific data engineering stack required for this role, including GCP, Databricks, and Airflow, which constitutes a significant gap. **⚠️ Critical Gaps:** - The candidate's experience is in on-premise infrastructure and basic AWS, while the role requires solid knowledge of the Google Cloud Platform (GCP) data stack. **✅ Strengths:** - Advanced Python proficiency demonstrated in complex automation and algorithmic projects. - Proven ability to architect and deploy end-to-end automated systems (e.g., JIT inventory system). - Strong problem-solving and systems-thinking mindset with a background connecting business logic to technical infrastructure. **❌ Missing Required:** Snowflake, Databricks, Airflow, DataStream, Google Cloud Platform (GCP)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong systems architect and automation engineer with impressive self-taught skills but has a complete technology stack mismatch for this Senior .NET Developer role. The position requires deep experience in .NET, C#, and modern JavaScript frameworks, none of which are present in the candidate's resume. **⚠️ Critical Gaps:** - .NET/C# Application Development - Front-End Web Development (JavaScript, Angular, CSS) **✅ Strengths:** - Systems Architecture - Process Automation (JIT Systems) - Proven Fast Learner & Self-Taught Engineer **❌ Missing Required:** .NET, C#, ASP.NET MVC, Entity Framework, AngularJS, SQL Server, TFS, CSS, HTML5, JQuery, AJAX

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is a very strong technical fit with proven, self-taught experience in core AI/LLM infrastructure, systems architecture, and data analysis using Python. The primary weakness is the lack of specific Oil & Gas domain knowledge, but a demonstrated history of rapid learning and applying technical skills to new complex domains (Finance, Supply Chain) strongly mitigates this risk. **✅ Strengths:** - Hands-on experience self-hosting and optimizing LLMs - Advanced proficiency in Python for automation and data analysis (Pandas/NumPy) - Proven ability to architect and deploy complex, automated systems from scratch **❌ Missing Required:** Knowledge of technical concepts from the oil and gas sector (geology, drilling, completion, production)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato possui uma forte aderência à maioria dos requisitos, com excepcional experiência prática em arquitetura de sistemas, automação com Python e infraestrutura de IA, evidenciada pela auto-hospedagem de LLMs. Sua trajetória de carreira e capacidade de aprendizado rápido são notáveis. A principal lacuna é a ausência de experiência direta com Databricks, um requisito mandatório, o que representa um risco, embora mitigado por sua comprovada habilidade em dominar novas tecnologias. **⚠️ Critical Gaps:** - Databricks (Requisito mandatório "imprescindível" não encontrado) **✅ Strengths:** - Arquitetura de Sistemas e integração de ponta a ponta - Experiência prática com infraestrutura de IA (LLMs) - Automação e desenvolvimento em Python em ambientes de produção **❌ Missing Required:** Databricks, Vivência em ambientes de nuvem (além de noções básicas)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is an exceptionally strong technical fit, with deep, self-taught experience in AI, systems architecture, and industrial automation aligning perfectly with the role's technical needs. However, the profile shows critical gaps in the core people management and commercial responsibilities (proposals, negotiation) required for a Project Coordination role. **⚠️ Critical Gaps:** - People Management (feedback, PDIs, salary) - Commercial Experience (proposals, negotiation) **✅ Strengths:** - Deep practical AI/GenAI experience (self-hosted LLMs) - Strong systems architecture and process automation background - Proven fast learner with a track record of mastering new domains **❌ Missing Required:** Elaboração de propostas comerciais, Negociação comercial, Alocar e gerenciar recursos da equipe, Conduzir feedbacks, apoiar a elaboração de PDIs

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate is an exceptionally strong fit for Radix's talent pool, demonstrating deep, hands-on expertise in multiple target areas including Machine Learning (self-hosted LLMs), Data Engineering (quant bots), and Industry 4.0 (automated JIT systems). The career trajectory shows a clear and intentional progression towards complex, high-value technical and AI-focused roles, aligning perfectly with the company's stated focus. **✅ Strengths:** - Hands-on AI/ML infrastructure experience (self-hosting LLMs) - Proven ability to architect and build production-grade automated systems from scratch (JIT inventory) - Strong background in Data Science and quantitative analysis (Python, Pandas/NumPy) **❌ Missing Required:** Fullstack Development

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] The candidate is a perfect fit for Radix's talent pool, demonstrating deep, practical expertise in several of the company's stated areas of interest, including Automation, Process Engineering, and Planning. His career trajectory shows a deliberate progression towards high-value systems architecture and AI infrastructure, making him a versatile and forward-looking asset for diverse, interdisciplinary projects. **✅ Strengths:** - Expertise in designing and deploying end-to-end automation systems - Proven ability to self-teach and apply emerging technologies like AI/LLMs - Strong foundation in engineering, supply chain, and finance, providing valuable cross-domain perspective

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] O candidato possui uma sólida formação em automação de software, IA e sistemas de TI, mas carece de experiência crítica no domínio de automação industrial exigido. Há uma lacuna fundamental entre sua especialização em infraestrutura de software/IA e os requisitos do trabalho em sistemas SCADA, protocolos industriais (IEC 61131-3) e software de modelagem civil/estrutural. **⚠️ Critical Gaps:** - Domínio de Automação Industrial vs. Automação de Software/TI - Software de Engenharia Civil/Estrutural (SAP2000, etc.) **✅ Strengths:** - Capacidade comprovada de aprendizado rápido e auto-didatismo - Base educacional em Engenharia de Mecatrônica e Automação - Experiência em automação de sistemas e processos com Python **❌ Missing Required:** Desenvolvimento de lógicas em linguagem IEC 61131-3, Conhecimentos e configuração de sistemas SCADA, Conhecimento avançado em modelagem computacional (SAP2000, Civil3d, etc.), Ferramentas de desenho 2D (AutoCAD, Microstation)

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate demonstrates strong foundational skills in systems architecture and AI infrastructure, evidenced by self-hosting LLMs and building automated JIT systems. The career trajectory shows a deliberate and successful move into AI. While specific frameworks like LangChain are missing, the candidate's proven fast-learning capabilities and deep understanding of underlying principles make them a high-potential fit. **✅ Strengths:** - Hands-on Generative AI experience (self-hosted LLMs) - Proven ability to architect and build complex, automated production systems - Strong proficiency in Python for automation and data handling **❌ Missing Required:** LangChain, TensorFlow, PyTorch, Scikit-learn

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato é um arquiteto de sistemas e engenheiro de automação altamente qualificado, com comprovada capacidade de aprendizado rápido e implementação de tecnologias complexas. No entanto, há uma lacuna crítica na experiência de domínio, pois ele não possui os 3 anos necessários em Oil & Gas, o que é um requisito fundamental para a função. **⚠️ Critical Gaps:** - Experience in Oil & Gas domain **✅ Strengths:** - Exceptional technical aptitude and proven fast learner - Strong background in systems architecture and automation - Engineering degree and fluent English match requirements perfectly **❌ Missing Required:** Minimum 3 years of experience in Oil & Gas, Experience in an operational site or similar industrial environment

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong Systems Architect and a proven fast learner with a solid foundation in Python, SQL, and AWS basics. However, this is a Data Engineering role with a critical requirement for Apache Spark and PySpark, which represent a major gap in the candidate's current skillset. **⚠️ Critical Gaps:** - Apache Spark - PySpark and distributed processing **✅ Strengths:** - Strong Python experience in automation and analytics - Systems architecture and integration mindset - Proven fast learner with a track record of self-teaching complex domains **❌ Missing Required:** Data Lake architectures, dimensional modeling

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong technologist and systems architect, but this role is fundamentally a non-technical Project Management/Knowledge Management position. While the candidate's Python skills are a match, there is a critical gap due to the missing mandatory PMP/PRINCE2 certification and a lack of experience with the required corporate software stack (SharePoint, MS Project). The candidate's career trajectory is moving towards deep tech and AI, while this role focuses on process administration. **⚠️ Critical Gaps:** - Missing mandatory project management certification (PMP or PRINCE2) **✅ Strengths:** - Strong Python knowledge with demonstrated application in automation - Extensive experience (10+ years) in technical and analytical roles - Proven ability to self-teach and deliver complex systems (JIT inventory, LLM clusters) **❌ Missing Required:** Conhecimento intermediário em MS Project, Conhecimento intermediário em Teams/Sharepoint/Planner, Certificação PRINCE2 Practitioner ou PMP®

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] O candidato demonstra fortes qualidades de liderança técnica, arquitetura de sistemas e automação, que são relevantes para a senioridade do cargo. No entanto, existe uma lacuna crítica na stack de tecnologia principal; a vaga exige proficiência em NextJS/NodeJS, Java e React, enquanto a experiência do candidato é quase exclusivamente em Python e infraestrutura. **⚠️ Critical Gaps:** - A experiência de desenvolvimento do candidato é em Python, enquanto a vaga requer especificamente o ecossistema JavaScript (NextJS/NodeJS, React) e Java. Esta é uma incompatibilidade de domínio de programação fundamental. **✅ Strengths:** - Liderança técnica comprovada como fundador e chefe de engenharia. - Experiência profunda em arquitetura de sistemas complexos e automação (JIT, Trading Bots). - Mentalidade de 'metal-up' e foco em ROI, conectando tecnologia a resultados de negócios. **❌ Missing Required:** NextJS/NodeJS, Java, React/React Native, Azure DevOps, testes unitários

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate demonstrates strong inferred skills in data integration, automation, and algorithms from complex, self-directed projects. However, the profile has two critical gaps: no experience with the required 'Cognite Data Fusion (CDF)' platform and a lack of the required advanced Spanish language skill, making it a poor fit despite the strong foundational engineering talent. **⚠️ Critical Gaps:** - Missing required experience in Cognite Data Fusion (CDF) platform. - Does not meet the advanced Spanish language requirement. **✅ Strengths:** - Proven ability to architect and build complex, automated systems from scratch (JIT inventory). - Strong algorithmic and data analysis skills demonstrated through quantitative trading bots. - Fast learner with a track record of self-teaching and applying complex technologies (AI clusters, trading). **❌ Missing Required:** Experiência com Cognite Data Fusion (CDF), Espanhol avançado para conversação, Experiência com data warehouse

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven systems architect and a fast learner in the AI/Infrastructure space, but possesses a completely different technology stack (Python, Docker, Shell) than what is required for this role (.NET, C#, SQL Server, ASP.NET). This is a fundamental mismatch, representing a critical skill gap. **⚠️ Critical Gaps:** - Primary development stack: Candidate is Python/Infrastructure, role requires .NET/C# full-stack. - Web development experience: Candidate has no demonstrated experience with required frontend (Angular, JS, CSS, HTML) or backend web frameworks (ASP.NET MVC, Web API). - Database technology: Role requires deep SQL Server experience, which is not present in the resume. **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex technologies. - Strong experience in systems architecture and building automated, production-grade systems from scratch. - Fluent in English, meeting a key communication requirement. **❌ Missing Required:** .NET, SQL, C#, ASP.NET MVC, Entity Framework, AngularJS, CSS, HTML5, JQuery, TFS

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with excellent backend Python and infrastructure skills, aligning with the core problem-solving aspects of the role. However, a critical gap in required frontend technologies (React/Angular) and missing experience with specified data platforms (Snowflake/Databricks) and cloud services (Azure) makes them a partial fit for a consultant role requiring broad technical reference. **⚠️ Critical Gaps:** - Frontend development (React, Angular) **✅ Strengths:** - Deep expertise in Python for backend and automation - Proven ability to architect and build complex, automated systems from scratch (JIT, LLM clusters) - Strong background in connecting business needs (Finance, Supply Chain) to technical solutions **❌ Missing Required:** Experiência com Cloud Azure, Experiência com plataformas de dados (Snowflake, Databricks, Cognite)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect with impressive technical and problem-solving skills, but lacks any direct experience in formal Quality Management, QA/QC processes, or team supervision in a quality-focused role. While possessing transferable skills like project management and leadership, the fundamental gap in the core job domain makes this a weak match. **⚠️ Critical Gaps:** - Quality Management Domain: The candidate's experience is in technical systems architecture and engineering, while the role is focused on process-driven Quality Management, assurance, and compliance. **✅ Strengths:** - Excellent problem-solving mindset demonstrated through complex system builds - Fluent English (C2 Certified) - Proven fast learner with a track record of mastering new technical domains **❌ Missing Required:** Liderança de equipes de qualidade (experience leading quality teams), Experiência em supervisão de pessoal de QA e QC em projetos (experience supervising QA/QC personnel)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable systems architect and fast learner with a strong background in automation, Python, and data-driven systems. However, there is a critical, insurmountable gap: the complete lack of any experience with 3D data, which is the core competency of the role. While he has transferable skills in data modeling and systems integration, the domain is a complete mismatch. **⚠️ Critical Gaps:** - Lacks any demonstrated experience in the 3D data domain, which is the primary function of this specialized role. **✅ Strengths:** - Strong Systems Architecture and Automation skills - Proven ability to build production systems from scratch - Fluent English and strong collaboration skills **❌ Missing Required:** Ampla experiência em contextualização, modelagem e ingestão de dados 3D, Experiência no trabalho com modelos industriais 3D e hierarquias de ativos, Familiaridade com plataformas de dados industriais

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Pro] Candidate demonstrates exceptional foundational skills in Python, SQL, and end-to-end data systems architecture by building a complex JIT automation engine from scratch. While direct experience with specific enterprise-scale cloud data services is limited, their proven ability to rapidly self-teach and build robust infrastructure (Docker, local AI clusters) makes them a high-potential fit who can quickly master the required tools. The career trajectory shows a deliberate and successful progression towards complex systems and AI. **✅ Strengths:** - Proven ability to architect and build complex, automated data systems from scratch (JIT Engine) - Strong, demonstrated proficiency in Python and SQL for automation and data manipulation - Rapid learning and adaptation to new, complex technologies (e.g., self-hosted AI) **❌ Missing Required:** 3+ years experience with data engineering in enterprise cloud environments (experience is primarily self-owned/custom infrastructure)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is disqualified due to not meeting two hard requirements: they are not based in a required country (U.S., Canada, etc.) and they lack the mandatory Master's/PhD and professional expertise in Environmental Science. While they have strong Python skills, their entire professional and academic background is in engineering and business systems, making them a poor fit for a subject matter expert role in environmental science. **⚠️ Critical Gaps:** - Lack of any academic or professional background in Environmental Science. - Does not meet the Master's/PhD requirement for the specified field. **✅ Strengths:** - Strong Python skills for automation and data analysis **❌ Missing Required:** Master’s or PhD in Environmental Science, Expertise in climate modeling, ecology, or sustainability, Based in the U.S., Canada, New Zealand, U.K., or Australia

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong systems architect with proven end-to-end project ownership and deep experience in data pipelines and automation, aligning with the core of the role. While lacking direct production experience with the specified FastAPI and RAG stack, his demonstrated ability to self-teach and build complex AI infrastructure suggests he can bridge this gap quickly. **✅ Strengths:** - End-to-end system ownership from concept to production - Deep experience with data pipelines and automation in a business context - Proven fast learner with a track record of mastering new technical domains (AI infra, algorithmic trading) **❌ Missing Required:** Python + FastAPI production experience, LLM & RAG stack (embedding stores, chunking, re-rank, hybrid search), Observability & eval tooling (e.g., Langfuse-style telemetry), REST/GraphQL and WebSocket/SSE (not explicitly listed)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong strategic fit, demonstrating extensive experience in systems architecture, AI infrastructure (self-hosted LLMs), and bridging business needs with technical solutions. Their career trajectory aligns perfectly with the role's focus on translating business strategy into technology. The primary gap is a lack of explicitly stated proficiency in specific enterprise AI/ML frameworks like TensorFlow or PyTorch, though their fast-learner profile mitigates this concern. **✅ Strengths:** - Proven ability to architect and build complex, resilient, automated systems from the ground up. - Deep, hands-on experience with AI infrastructure, including self-hosting LLMs, demonstrating a 'metal-up' understanding. - Clear career progression towards senior technical and strategic AI roles, showing high motivation and adaptability. **❌ Missing Required:** Proficiency in AI frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), Proficiency in cloud platforms (candidate has 'AWS Basics' but not 'Proficiency')

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong conceptual match, demonstrating proven technical leadership, systems architecture skills, and a strategic mindset aligning business with technology. However, there is a critical gap in the specific Azure data stack (Databricks, ADLS, Event Hubs, Medallion) required for this role, though their AWS and on-prem AI experience indicates high adaptability and fast-learning potential. **⚠️ Critical Gaps:** - The core requirement is deep, advanced expertise in the Azure data ecosystem (Databricks, ADLS, Event Hubs), while the candidate's cloud experience is listed as 'AWS Basics' and on-premise infrastructure. **✅ Strengths:** - Proven technical leadership and strategic vision as a founder. - Strong systems architecture and automation skills (Python, CI/CD, Docker). - Demonstrated ability to self-teach and apply complex technologies (self-hosted LLMs). **❌ Missing Required:** Experiência avançada com Azure Data Lake Sorage e Auzre Databricks, Experiência avançada comzure Event Hubs, Experiência avançada com a Arquitetura Medallion, Experiência com streaming de dados

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect and Engineer, but the role is for a Design Teacher. There is a fundamental mismatch in professional experience, as the candidate has no background in teaching, curriculum development, or classroom pedagogy, which are the core requirements of the position. While their engineering degree is technically a match, their career trajectory is moving deeper into technology and away from education, making this a poor fit. **⚠️ Critical Gaps:** - The role requires a teacher with pedagogical experience; the candidate is an engineer/architect. - The job requires experience with the educational 'design cycle', not technical systems architecture. **✅ Strengths:** - Bachelor of Engineering degree meets one of the required fields - Proven ability to self-learn complex topics - Strong technical/builder background which could be tangentially relevant to a 'Maker Space' **❌ Missing Required:** Experience teaching Design or related subjects, Strong knowledge of and experience with classroom pedagogy

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly technical systems architect with a career trajectory moving towards AI infrastructure, while the job is a process-driven financial operations role within the insurance domain. Despite strong analytical abilities and fluent English, there is a fundamental mismatch in core skills, experience, and career goals. The role requires specific insurance payroll and policy system knowledge, which the candidate lacks entirely. **⚠️ Critical Gaps:** - Core Job Function: The candidate is a systems builder and architect, while the role is for an operational analyst executing predefined processes in a specific business domain (Insurance Payroll). **✅ Strengths:** - Fluent English (C2 Certified) - Strong analytical and quantitative background - Proven fast learner with experience in complex systems **❌ Missing Required:** Experience with payroll audits, Knowledge of insurance statutory rules, Experience with policy management systems

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled technical architect with a strong background in systems automation and AI infrastructure. However, this profile is a significant mismatch for the Engagement Manager role, which prioritizes executive client relationship management, P&L oversight for client accounts, and leadership of large delivery teams—areas where the candidate has no demonstrated experience. The role is primarily commercial and operational, while the candidate's expertise is deeply technical and hands-on. **⚠️ Critical Gaps:** - The role is client-facing and commercial (Engagement Manager), while the candidate is a hands-on technical architect and builder. - Lack of experience managing large teams and client-facing service delivery programs. **✅ Strengths:** - Impressive technical depth and fast learning ability - Strong understanding of system architecture from metal-up - Proven ability to deliver complex technical projects autonomously **❌ Missing Required:** Sólida experiência em Gestão de Projetos e Contratos de Serviços (Solid experience in Project and Service Contract Management)

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is automatically disqualified due to a hard filter: the job requires fluency in Portuguese, Spanish, and English, but the candidate does not list Spanish. Furthermore, there is a fundamental career path mismatch; the candidate's resume shows a deep, hands-on technical trajectory in systems architecture and AI, while the role is a non-technical, relationship-driven Customer Success position. **⚠️ Critical Gaps:** - Missing mandatory language requirement: Spanish. - Role mismatch: Candidate has a highly technical/architectural background, while the job is a non-technical customer relationship role. **✅ Strengths:** - Strong analytical and problem-solving skills demonstrated through building complex automated systems. - Proven ability to connect business logic to technical implementation. - Fluent in both English and Portuguese. **❌ Missing Required:** Spanish (Fluent), 3+ years of experience in Customer Success or Account Management, Experience in short-term rental, hospitality, or revenue management

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly skilled Systems Architect and automation expert but lacks the specific domain experience required for a QA Automation Engineer. There is a critical gap in required skills, including proficiency with standard QA tools (Playwright, Selenium) and the specified programming languages (PHP, JS, C#). While the candidate demonstrates a strong aptitude for automation and is a proven fast learner, their career trajectory is divergent from this specialized testing role. **⚠️ Critical Gaps:** - Role Mismatch: Candidate is a Systems/Infrastructure Architect, not a QA Automation Engineer. **✅ Strengths:** - Proven ability to architect complex, fully automated systems from scratch - Strong problem-solving and systems-thinking skills - Demonstrated fast learner with experience in CI/CD and cloud basics **❌ Missing Required:** 5+ years of experience as a QA Automation Engineer, Proficiency in programming/scripting languages such as PHP, JavaScript, or C#, Hands-on experience with tools like Playwright, Robot, Selenium, or Postman, Familiarity with performance testing tools like JMeter or LoadRunner

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable systems architect and fast learner, but possesses zero experience in the required Salesforce ecosystem (Health Cloud, Apex, LWC) or the healthcare domain. This creates a critical skill gap that makes them a poor fit despite their strong general engineering and infrastructure background. **⚠️ Critical Gaps:** - Candidate's experience is in Python, Infrastructure, and general Systems Architecture, while the role is exclusively for a Salesforce Developer. - The role requires experience in the Health sector, which the candidate does not have. **✅ Strengths:** - Proven fast learner with a track record of self-teaching complex technical domains. - Strong background in systems architecture and automation. - Experience building and deploying production-level systems from the ground up. **❌ Missing Required:** Salesforce Health Cloud, Apex, Lightning Web Components (LWC), Visualforce, Integration with EHR/EMR systems

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] While the candidate is fluent in English and has a strong entrepreneurial profile that matches the role's independent nature, there is a fundamental mismatch of profession. The role requires a language teacher, and the candidate is a highly specialized AI and Systems Engineer with no demonstrated experience, skills, or interest in education or pedagogy. His career is moving in the opposite direction of this role. **⚠️ Critical Gaps:** - Domínio da Carreira: Engenharia/IA vs. Educação/Ensino **✅ Strengths:** - Fluência em Inglês (C2) - Perfil Empreendedor / Fundador - Independência e proatividade **❌ Missing Required:** Qualquer habilidade ou experiência em ensino ou tutoria

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] The candidate is fundamentally a poor fit due to a critical domain mismatch and a hard language requirement failure. The role is for operational content moderation requiring Spanish, whereas the candidate is a highly technical Systems Architect with a background in infrastructure and automation, and no listed Spanish proficiency. **⚠️ Critical Gaps:** - The role is non-technical content safety and operations; the candidate's profile is deeply technical (AI infrastructure, systems architecture, automation). - The job requires Spanish proficiency, which the candidate does not possess. **✅ Strengths:** - Strong analytical and problem-solving skills from a technical domain. - Proven ability to learn complex subjects quickly (Fast Learner Bonus applied). - Experience with data analysis tools like Python/Pandas. **❌ Missing Required:** Spanish language proficiency, Experience in content moderation, QA, or a related field, Willingness to work with sensitive content (not explicitly stated by candidate)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate demonstrates strong architectural talent and a deep, fundamental understanding of AI systems by self-hosting LLMs, which is a powerful indicator of skill. However, there is a critical gap between their AWS/local infrastructure experience and the job's requirement for Azure, Databricks, and specific MLOps tools. While their proven fast-learning ability is a plus, the lack of direct experience with the required enterprise tech stack makes them a qualified, but not ideal, fit. **⚠️ Critical Gaps:** - Cloud platform mismatch: Candidate has AWS/On-premise experience, while the role requires Azure, Spark, and Databricks. **✅ Strengths:** - Deep, 'metal-up' understanding of AI infrastructure from self-hosting LLMs. - Proven ability to architect and build resilient, automated production systems from scratch. - Strong Python and quantitative background from algorithmic trading experience. **❌ Missing Required:** 7+ years of expertise in machine learning engineering (Candidate's experience is adjacent but not a direct match by title), Experience with specific MLOps and CI/CD frameworks (Orion, ArgoCD, Opsera), Competency with specified monitoring tools (Grafana, Dynatrace, ThoughtSpot)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong conceptual fit, demonstrating the ability to architect and build complex, automated systems from the ground up, including self-hosted LLMs. While they lack experience with the specific MLOps and observability tools listed (ArgoCD, Grafana, etc.), their proven track record as a fast learner and systems builder suggests they can acquire these skills rapidly. The career trajectory shows a clear and intentional progression towards this exact type of role. **✅ Strengths:** - Proven ability to architect, build, and deploy complex, end-to-end automated systems from scratch. - Deep, hands-on experience with core LLM infrastructure, demonstrating skills beyond just using APIs. - Strong problem-solving and self-learning capabilities across multiple technical domains (AI, trading, logistics). **❌ Missing Required:** MLOps tools (Orion, ArgoCD, Opsera), Monitoring/observability tools (Grafana, Dynatrace, ThoughtSpot), Azure (has AWS experience), Apache Spark, Databricks

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong systems architect and technical project leader with a proven ability to deliver complex systems from concept to production. While he exceeds the technical and project execution requirements, the resume shows a critical gap in external client-facing engagement management and sales collaboration, which are core functions of this role. **⚠️ Critical Gaps:** - External Client Engagement Management - Pre-Sales Support (SOW/RFP generation) **✅ Strengths:** - End-to-end Technical Project Execution - Financial Acumen & ROI Focus - Rapidly Learns Complex Technologies **❌ Missing Required:** Experience working with Sales to scope services projects, 1+ years of people management experience (mentoring direct reports is not demonstrated)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a poor fit due to a critical domain mismatch. While possessing a strong engineering degree, financial acumen, and supply chain expertise, the resume shows no experience in the energy sector or with substation projects, which is a core requirement. The candidate's project management experience is entrepreneurial and software-focused, not aligned with large-scale industrial projects as described in the job. **⚠️ Critical Gaps:** - The role requires experience with energy substation projects, a domain entirely absent from the candidate's background in e-commerce, finance, and AI. **✅ Strengths:** - Supply Chain & Procurement Expertise - Financial Analysis & Control - Proven ability to architect and build automated systems from scratch **❌ Missing Required:** Experiência com projetos de ubestações (subestações), Atuação com projetos de diferentes tamanhos, complexidades e formas de contratos, MS Project, ERP SAP

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a highly capable systems architect with proven experience in building complex, automated systems and a strong background in finance and risk management. However, there is a critical gap in direct experience with the specific Brazilian payment and credit products (PIX, TED, CCB) and Central Bank regulations, which are core requirements for this role. **⚠️ Critical Gaps:** - Experiência direta com produtos bancários e meios de pagamento brasileiros (PIX, TED, Open Finance, etc.) - Conhecimento em regulamentação do BACEN (Banco Central do Brasil) **✅ Strengths:** - Arquitetura de sistemas complexos e automatizados (JIT, Bots) - Forte background em finanças e análise quantitativa - Capacidade comprovada de aprendizado rápido em domínios técnicos **❌ Missing Required:** Gerenciamento de projetos em fintechs ou bancos digitais

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato possui forte alinhamento conceitual e de domínio, com vasta experiência em supply chain, automação de sistemas e análise quantitativa. No entanto, há lacunas críticas nas ferramentas de data science e BI especificadas, como a falta de experiência declarada com certos modelos preditivos e a ausência da certificação mandatória em Power BI, o que representa um risco. **⚠️ Critical Gaps:** - Certificação mandatória em Power BI não encontrada. **✅ Strengths:** - Experiência comprovada em arquitetar e implantar sistemas automatizados complexos de ponta a ponta. - Profundo conhecimento de domínio em Supply Chain, Planejamento e Controle (PCP) e logística. - Nível avançado de Python para análise de dados (Pandas/NumPy) e automação. **❌ Missing Required:** Experiência com modelos preditivos específicos (redes neurais, árvores de decisão, etc.), Proficiência em ferramentas de business intelligence (PowerBI), Certificação Power BI (e.g., PL-330)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is an impressive Systems Architect and a proven fast learner, but fundamentally lacks the primary required skill: 1-2+ years of professional Go programming experience. The role is for a Go language specialist, and the candidate's expertise is in Python and infrastructure. This critical language gap makes it a poor fit despite strong adjacent skills in automation and systems design. **⚠️ Critical Gaps:** - The role requires professional Go development experience, whereas the candidate's background is in Python and systems architecture. **✅ Strengths:** - Proven fast learner with a track record of mastering new technical domains (awarded +7 bonus) - Deep experience architecting and deploying automated, production-grade systems - Strong transferable background in systems integration and CI/CD pipelines **❌ Missing Required:** 1–2+ years of professional Go programming experience, Hands-on software engineering experience building and maintaining backend-style Go applications

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate has a strong background in systems architecture, Python-based quantitative analysis, and AI infrastructure. However, the role is for an 'R Engineer' and requires deep, hands-on experience with R and its data science ecosystem (tidyverse, ggplot2), which is completely absent from the resume. This represents a critical skill gap, making it a poor fit despite transferable skills in data analysis and AI. **⚠️ Critical Gaps:** - R programming for data analysis **✅ Strengths:** - Extensive experience with LLMs - Proven fast learner with a strong technical aptitude - Experience in quantitative analysis (using Python) **❌ Missing Required:** 2+ years of hands-on experience using R, Strong proficiency in R programming, Solid grounding in applied statistics... in R, Familiarity with common R ecosystems

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] O candidato demonstra forte pensamento arquitetônico, visão estratégica e experiência em projetar sistemas complexos do zero. No entanto, há uma lacuna crítica e fundamental na pilha de tecnologia principal: a vaga exige proficiência em .Net ou Java, enquanto toda a experiência do candidato é em Python, o que o torna um ajuste fraco para os requisitos técnicos específicos. **⚠️ Critical Gaps:** - Proficiência em linguagem de programação (.Net/Java vs. Python) **✅ Strengths:** - Design de arquitetura de sistemas de ponta-a-ponta - Visão estratégica e alinhamento com negócios - Resolução de problemas complexos e automação **❌ Missing Required:** iPaaS, Message Queues, Segurança (OAuth), Experiência com middleware, Conhecimento aprofundado de nuvem (Azure/AWS)

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] The candidate is a strong strategic builder with proven experience architecting automated systems and self-hosting AI infrastructure, aligning with the 'hands-on strategic leader' aspect of the role. However, there are significant gaps in the specified modern data stack (BigQuery, DBT, Looker, Segment), which are critical for managing the existing platform. While a proven fast learner, the lack of direct experience would create a steep learning curve. **⚠️ Critical Gaps:** - Experience with the core required data stack (DBT, Looker, Segment/Mixpanel) is absent. **✅ Strengths:** - Proven ability to architect and build automated, production-grade systems from scratch (JIT System). - Deep, hands-on experience with AI infrastructure and LLM deployment. - Strong business acumen and strategic mindset from founder experience. **❌ Missing Required:** 8+ years in data engineering/BI/analytics (experience is broader), 3+ years leading teams (experience is as a founder, slightly under 3 years), Expert SQL (BigQuery or similar), DBT (tests, CI/CD, exposures), Looker/LookML governance, Segment/Mixpanel experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong technical architect with proven experience in designing and deploying complex, automated systems from the ground up. However, there's a significant experience gap regarding the specific enterprise technologies required, such as Windows Server administration, ITIL, and formal project management. Their self-taught background and rapid progression suggest high adaptability, but they lack direct experience in the specified corporate IT environment. **✅ Strengths:** - Deep experience in systems architecture and automation (Python, JIT system) - Proven ability to self-host and manage complex infrastructure (LLM clusters) - Strong business and financial acumen from previous roles **❌ Missing Required:** Experiência em migrações de Sistemas Operacionais Windows Server, Conhecimento de processos ITIL, Background técnico em Workplace (PCs, Videoconferência), Gerenciamento de troca de equipamentos de videoconferência

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly technical Systems Architect, while the role is a non-technical Team Lead focused on people and process management. There is a critical domain mismatch, with no demonstrated experience in the core requirements of team supervision, performance coaching, or client-facing process reporting. The candidate's career is moving towards deeper technology, away from the required people management skills. **⚠️ Critical Gaps:** - The role requires a non-technical people manager, but the candidate is a senior technical systems architect. **✅ Strengths:** - Deep understanding of process automation. - Proven ability to self-teach complex domains. - Strong background in data analysis and system optimization. **❌ Missing Required:** 3-5 years of experience in team performance management (driving metrics, coaching, daily supervision)., Experience in client-facing communication regarding process performance., Direct people leadership experience (hiring, attrition management, performance reviews).

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a strong technologist with excellent infrastructure and automation skills but has a critical, disqualifying gap in the core requirement: SAP S/4HANA experience. His career trajectory is moving away from enterprise ERP systems towards bespoke AI infrastructure, making this a poor fit despite his technical aptitude and project leadership experience in other domains. **⚠️ Critical Gaps:** - SAP S/4HANA project experience **✅ Strengths:** - Strong experience with both on-premise and cloud infrastructure - Proven ability to architect and automate complex, production-level systems from scratch - Fluent in English, which is a listed differential for the role **❌ Missing Required:** Experience in managing large-scale ERP implementation or migration projects (5-8 years), Direct experience with SAP S/4HANA

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] O candidato é um arquiteto de sistemas e engenheiro de IA altamente qualificado, com profunda experiência em infraestrutura Linux e automação. No entanto, existe uma lacuna crítica, pois a função é 50% focada em auditoria e conformidade de TI (SOX, PCI, ISO 27001), uma área totalmente ausente no seu histórico. Além disso, falta-lhe a experiência necessária em administração de Windows Server e Active Directory, que são requisitos fundamentais para a outra metade da função. **⚠️ Critical Gaps:** - Experiência com auditoria e conformidade de TI (PCI, SOX, SOC 2, ITGCs) - A função é 50% focada em um domínio completamente diferente da experiência do candidato. **✅ Strengths:** - Profunda expertise em administração de sistemas Linux e automação - Histórico comprovado de arquitetura e construção de sistemas complexos do zero - Rápido aprendizado e adaptação a novas tecnologias (Fast Learner) **❌ Missing Required:** Administração de Windows Server, Active Directory, Experiência comprovada em suporte a auditorias, Familiaridade com frameworks de auditoria (PCI, SOX, etc.)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong technical architect with deep, hands-on experience in logistics automation (JIT systems) and a proven entrepreneurial mindset that fits the company culture. However, the role requires proven experience managing technical teams and a formal background in Six Sigma/Black Belt, which are significant gaps. His skills are a near-perfect match for the problem domain, but not for the specified managerial and process framework. **⚠️ Critical Gaps:** - A role focado em gestão de equipes e o candidato apresenta um perfil mais de arquiteto/fundador individual. **✅ Strengths:** - Profunda experiência em automação de logística e supply chain (sistemas JIT) - Mentalidade de dono e foco em ROI, comprovado pela fundação de um negócio próprio - Forte habilidade técnica (Python, Automação) aplicada a problemas de negócio **❌ Missing Required:** Experiência comprovada liderando equipes técnicas, Formação complementar em Black Belt, Six Sigma, Espanhol intermediário

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is vastly overqualified in strategic architecture and engineering, but lacks direct experience in the specific operational tools and procedural frameworks (NMS, ITIL, ITSM) required for this monitoring role. His career trajectory is moving towards high-level system design, making this hands-on operational position a fundamental mismatch in both seniority and function. **⚠️ Critical Gaps:** - Role Mismatch: Candidate is a senior-level Systems Architect and Engineer, while the job is a junior/mid-level operational Monitoring Analyst. - Process vs. Build: The candidate's experience is in designing and building autonomous systems from the ground up, not in following procedural frameworks like ITIL to manage incidents in an existing environment. **✅ Strengths:** - Deep expertise in system automation and infrastructure design. - Proven fast learner with a track record of self-teaching complex domains (AI, Quant Trading). - Strong foundation in Python and scripting, relevant for understanding system behavior. **❌ Missing Required:** Ferramentas NMS - como Zabbix, Grafana, PRTG, Conhecimentos básicos de ITIL, Utilização e ferramentas de ITSM