[ANALYSIS_REPORT] [Model: gemini-cli] The candidate operates in a modern tech stack (Python, Cloud, AI, Automation), whereas the role is strictly focused on legacy systems (COBOL, PowerBuilder). While the candidate possesses general SQL knowledge and engineering capability, the fundamental languages required for this role are completely outside their domain of expertise.

[ANALYSIS_REPORT] [Model: gemini-cli] Critical mismatch in core technology stack. The candidate is a strong Python/Infrastructure strategist, while the role requires a dedicated Java/Spring developer. Although the candidate possesses transferable architectural skills (Docker, CI/CD, System Design), the absence of Java, Spring, and enterprise messaging experience makes this a poor fit without a complete language transition.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate has a strong technical foundation in Infrastructure, Automation, and adjacent Identity Security concepts (SSO, RBAC, OIDC), supported by a proven 'Fast Learner' trajectory. However, the role is a specialized Consultant position explicitly requiring 4+ years of specific PAM (CyberArk) tool expertise and Spanish language proficiency, both of which are absent from the resume.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong fit for the Backend, Integration, and Business Logic requirements, leveraging extensive Python automation and relevant Finance/Supply Chain domain experience. He fulfills the 'NodeJS or Python' core requirement via Python. However, a significant domain gap exists in Frontend development (React), which is a hard requirement. While he is a 'Fast Learner' capable of adapting to SQL Server quickly, the lack of Javascript/Frontend history specifically lowers the immediate match score.

[ANALYSIS_REPORT] [Model: gemini-cli] Exceptional domain fit: The candidate's background in 'JIT inventory engines' and Supply Chain Analytics is a near-perfect match for the role's 'reverse supply chain' focus. However, the role is a 'Senior Fullstack' position specifically for Ruby on Rails and Frontend (HTML/CSS/JS), whereas the candidate is a specialist in Python/Infrastructure. While the candidate is a proven fast learner (Systems Architect), the gap between Python Backend and Senior Rails Fullstack is significant enough to impact immediate productivity.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong domain alignment (Finance, Supply Chain, SQL) and general data capability (Pandas, Analytics). However, the role strictly requires 'Expert' level proficiency in the Microsoft/SAP BI stack (PowerBI, DAX, S4 Hana), which are specific tools absent from the resume. The candidate is a 'Builder' (Python/Infra) rather than the requested 'Enterprise Reporter' (BI/SAP).

[ANALYSIS_REPORT] [Model: gemini-cli] Strong architectural match. The candidate's specific background in 'Self-hosted LLMs' and 'Algorithmic Trading' (Fintech) aligns perfectly with the 'Staff Engineer' requirements for decision-making and 'build vs buy' strategy. His experience optimizing local AI clusters demonstrates deep technical depth beyond simple API integration. The gaps are specific modern data infrastructure tools (Graph/Vector DBs) which are easily bridgeable for someone who builds custom crypto trading bots and self-hosted AI stacks.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a highly capable Systems Architect with a strong foundation in data logic (SQL, Python, Supply Chain Analytics), but lacks the specific 2+ years of mandatory experience in the core Microsoft stack (Power BI, Azure, Databricks) required for this role. While his cloud (AWS) and data (Pandas) skills are adjacent and he is a fast learner, the role specifically demands seniority in tools he has not listed.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a highly capable 'Fast Learner' with strong Python, Automation, and Infrastructure skills (self-hosted LLMs, JIT systems). However, there is a significant hard-skill gap: the role explicitly demands 'Solid knowledge' in Ruby on Rails, whereas the candidate is a Python specialist. Additionally, specific requirements for Analytical Databases and Data Streaming are not evidenced, despite adjacent experience in financial data analysis.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate has a strong foundational fit (Mechatronics Engineering, ERP experience) and excellent 'Digital Transformation' potential due to automation/dev skills. However, the profile is currently specialized in Software/AI/Supply Chain, lacking specific, recent evidence of Industrial Maintenance methodologies (RCM) and the strictly required SAP/PM module implementation experience.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong match for the Python and Architecture aspects (Product Thinking, Autonomy) but has a critical gap in the Frontend domain (React/TypeScript), which is 50% of this Fullstack role. Additionally, the candidate self-assesses as having only 'Basic' AWS knowledge, whereas the role requires solid experience with specific cloud-native services (Lambda, Kafka, DynamoDB).

[ANALYSIS_REPORT] [Model: gemini-cli] Major role mismatch. The candidate is a Python-based Systems Architect/Builder, whereas the role specifically requires a Senior C# SDET with 10+ years of dedicated QA experience. While the candidate has strong 'Fast Learner' traits and cloud/API knowledge (AWS, Systems Integration), the lack of C# proficiency and specific long-term QA/SDET tenure makes this a difficult pivot without significant ramp-up.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a strong 'Fast Learner' with impressive self-taught architectural achievements (JIT systems, Local LLMs). However, for a 'Lead SRE' role, the admission of 'AWS Basics' versus the required 'Deep Expertise' is a significant gap. Additionally, while Docker is present, specific 'Kubernetes' orchestration experience at scale is missing. The candidate is a high-potential Systems Architect but lacks the specific tenure in high-scale cloud operations required for a Lead SRE position.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong architectural mindset and FinTech domain experience (Algorithmic Trading, Financial Analysis) align excellent with the 'Global Bank' context. The candidate demonstrates high 'Fast Learner' potential (self-hosted LLMs, automated JIT). However, significant technical stack gaps exist for a 'Senior' role: the candidate is Python-centric, whereas the role specifically utilizes Go/Java/Kotlin/Elixir. Additionally, enterprise-scale distributed systems tools (K8s, Kafka) are missing.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a strong architectural match with proven experience in complex system design (AI clusters, Algorithmic Trading) and Python mastery, fitting the 'Systems' aspect well. The 'Fast Learner' trait (self-hosted LLMs) significantly mitigates infrastructure gaps like Kubernetes. However, the specific requirement for Node.js/TypeScript and 'Deep' AWS experience (vs. candidate's 'Basics') creates a stack mismatch for a Senior role.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is an excellent cultural match for the 'AI-First' and 'Execution' pillars, with strong Infrastructure and Python-based Architecture skills. However, the role demands immediate 'Senior-level' hands-on capability to review and write code in the Web Stack (PHP, Node, React, TypeScript). The candidate is a Python/Data specialist, creating a critical technical gap for the required daily code reviews and mentorship, despite his high potential and adjacent backend knowledge.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate possesses a powerful combination of Supply Chain domain expertise (MITx MicroMasters), Financial Analysis background, and advanced Engineering skills. While the role asks for 'Advanced Excel', the candidate's mastery of Python/Pandas for financial modeling and automated inventory systems demonstrates a superior analytical capability ('Fast Learner' trait). The primary gap is the recent career trajectory focus on Systems Architecture rather than traditional FP&A routines, but the foundational skills are fully present.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate significantly exceeds the technical requirements (Automation/RPA, Analytics) and meets the 'Diferenciais' (E-commerce, Process Improvement) perfectly. His background in 'Algo Trading' and building 'JIT Systems' proves he can automate the core reconciliation tasks rather than just performing them manually. The main gap is the specific 'Accounting' domain knowledge (tax rules, formal classification) vs his Engineering background, but his 'Fast Learner' trait suggests he can master CNAB/Billing logic rapidly.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the Python legacy codebase and backend systems architecture. The candidate's 'Fast Learner' profile (self-taught AI/LLM clusters, Algorithmic Trading) aligns well with the requirement to 'Rapidly learn... internal tools'. However, the lack of 'Golang' is a significant hard skill gap for a Senior role specifically focused on migrating *to* Go. GraphQL is also missing but is listed as a 'plus' or learnable domain.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match on core Python, Infrastructure (Terraform/Docker), and System Architecture. The candidate's background in 'metal-up' architecture and self-hosted AI clusters demonstrates the high-level 'Fast Learner' trait required to bridge gaps. However, specific requirements for the 'Django' web framework, 'Kubernetes' orchestration (distinct from Docker), and 'React' are missing from the resume. The 'AWS Basics' claim may also be underweight for the specific services (SNS/SQS/EKS) requested.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for 'Systems' and 'Python' requirements. Candidate demonstrates high 'Fast Learner' potential (transitioning from Supply Chain to Quant Trading to Self-Hosted AI), which mitigates the lack of specific 'Browser' domain experience. Meets core requirements for Architecture, Linux, and Automation. Gaps are primarily in specific enterprise orchestration tools (Kubernetes) and the niche 'Chromium' domain, both of which are listed as 'Preferred' or 'Plus' in the JD.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a highly capable Systems Architect with strong Python and automation skills, but lacks the specific enterprise Data Engineering stack required for a 'Lead' role. While his JIT/Trading experience involves data logic, he is missing critical specific hard skills defined in the job description (Snowflake, Airflow, Streaming). He would likely succeed as a generalist Senior Engineer but would face a steep learning curve to lead a team specifically on the Snowflake/Data Lake stack immediately.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a highly technical Builder/Architect, whereas the role is a process-focused Agile Product Owner. While the candidate's experience as a Founder covers the essence of 'product ownership' and they have the aptitude to learn the tools immediately, they strictly lack the required 3-5 years of formal 'Product Owner' job title history, specific Agile certifications (CSPO/CSM), and explicit advanced experience with project management tools like Rally or Jira.

[ANALYSIS_REPORT] [Model: gemini-cli] O candidato é vastamente superqualificado (perfil Sênior/Engenharia) para uma vaga Júnior Administrativa. Possui competências de dados e finanças (Python, Pandas, Modelagem de ERP, Análise Financeira) que excedem em muito os requisitos de Excel/Google Sheets. A única lacuna técnica real é o software específico 'Conta Azul' e as rotinas operacionais de secretariado/BPO (entrada de dados manual), visto que seu foco tem sido automação e estratégia.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate shows strong 'Figure it out' aptitude (Founder, Self-hosted AI, JIT systems) and aligns well with the automation/Python/Terraform requirements. However, there are critical gaps for a 7+ year Senior role: 'AWS Basics' is insufficient for a role requiring deep design/scale expertise, and 'Kubernetes' (a core requirement to 'Own' clusters) is missing entirely. Additionally, the specific 'LAMP' (PHP/Apache) track record is absent.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate demonstrates strong alignment with core Python, Systems Architecture, and LLM Infrastructure (self-hosting) requirements. The 'Fast Learner' trait and success in 'metal-up' automation suggest he can rapidly bridge the specific application-layer gaps (LangChain, RAG). His experience optimizing local AI clusters proves he understands the heavy lifting behind the API abstractions.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match driven by heavy overlap in Domain (Fintech/Algo Trading) and Language (Python). The candidate's background as a Founder/Architect building production-grade automation aligns well with the Senior Backend requirements. While specific enterprise scaling tools (Kafka, Redis) are missing from the resume, his 'Fast Learner' profile (self-hosting AI clusters, trading bots) suggests he will master the distributed systems stack rapidly.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong foundational match in Python, Shell, Docker, and Terraform (IaC). The candidate's background in Algorithmic Trading and self-hosting AI clusters demonstrates the required 'Fast Learner' aptitude and high-level engineering capability. However, the role is specifically for a 'Senior AWS' engineer, and the candidate self-assesses as having 'AWS Basics' while missing specific AWS-native IaC tools (CDK, CloudFormation) and Kubernetes, which are critical for this specific platform engineering role.

[ANALYSIS_REPORT] Strong match on core engineering principles, Python automation, and infrastructure-as-code (Terraform). The candidate's experience with 'Local AI Clusters' and Docker suggests a rapid learning curve for Kubernetes/EKS. However, the requirement for 'Deep hands-on knowledge of MongoDB' is a significant hard skill gap, as the candidate only lists SQL. The role requires specific production-grade scaling experience which is not explicitly evidenced, though the 'Fast Learner' trait mitigates this slightly.

[ANALYSIS_REPORT] Critical domain mismatch. The candidate is a Senior Solutions Architect/Engineer, while the position is an entry-level Receptionist role in Hospitality. Although the candidate possesses the auxiliary requirements (English fluency, general computer literacy), they lack the specific industry experience requested and are vastly overqualified for the core responsibilities.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong cultural fit regarding the 'AI/Automation' mindset and 'Fast Learner' traits, which the JD explicitly values. However, there is a critical hard-skill mismatch: the role strictly requires 3-6 years of .NET and Angular experience. The candidate's expertise is deeply rooted in Python, Systems Automation, and Infrastructure, with no evidence of commercial Full-Stack Web Application development or the specific required stack.

[ANALYSIS_REPORT] The candidate is technically overqualified (Python/Automation vs. Excel) and possesses strong adjacent Supply Chain context. However, the resume focuses on high-level Systems Engineering and Architecture rather than the specific manual/operational financial tasks required (Billing, Reconciliation, Credit Analysis). While the candidate could likely automate the role, they lack the specific industry experience in Freight Forwarding (Agente de Cargas) and the recent operational track record requested.

[ANALYSIS_REPORT] Critical stack mismatch. This is a specialized Microsoft stack role requiring 'Expert' Azure Networking and 'Advanced' legacy .NET 4.6 experience. Your profile is built on a modern Linux/Python/AI stack. While Terraform and general CI/CD knowledge align, you lack the specific legacy framework (.NET 4.6) and cloud provider depth (Azure vs. AWS Basics) required for a Senior position in this environment.

[ANALYSIS_REPORT] [Model: gemini-cli] Critical skill mismatch. The candidate is a highly capable Software Engineer and Architect (Python, AI, Cloud) who builds custom solutions, whereas the role is a Functional SAP Analyst requiring specific configuration knowledge of a proprietary ERP system. While the candidate has excellent domain knowledge in Finance and Supply Chain (Purchase Planning, Trading), they completely lack the mandatory technical hard skills (SAP parametrization) required for a Mid-level ('Pleno') SAP role.

[ANALYSIS_REPORT] [Model: gemini-cli] High-level mismatch in technical stack. The candidate is a senior Python/Infrastructure/Data Architect, while the position requires a Senior Fullstack JavaScript specialist (React/Node.js) with Mobile development (React Native) experience. While the candidate has strong architectural and 'fast learner' traits (self-hosted systems, JIT automation), the specific requirement to mentor others in React/Mobile development constitutes a 'totally missing domain' per the evaluation rules.

[ANALYSIS_REPORT] [Model: gemini-cli] Major domain mismatch. The candidate is a senior Python-based Systems/Data Architect, whereas the role strictly requires a Senior Fullstack JavaScript & Mobile Developer. While the candidate has strong engineering fundamentals (Architecture, APIs, SQL, CI/CD), they completely lack the core hard skills for this specific role: Mobile Development (React Native), Frontend (React.js), and the specific Backend stack (Node.js/TypeScript).

[ANALYSIS_REPORT] Candidate is a highly strong match for the Automation, API Integration, and AI aspects of the role. His 'code-first' automation skills (Python) are explicitly listed as a differentiator, effectively mitigating the lack of specific 'Low-code' experience. His Supply Chain background provides excellent context for process mapping. Main gaps are specific commercial RPA suites (UiPath/Power Automate) and Power BI, but his deep technical aptitude suggests he can master these rapidly.

[ANALYSIS_REPORT] Major misalignment in technical stack and language requirements. The role is a specialized SAP Technical Lead position requiring deep knowledge of the SAP ecosystem (ABAP, BASIS, S/4HANA), whereas the candidate is a Python/AI/Infrastructure architect. While the candidate possesses strong Supply Chain domain knowledge, they lack the specific proprietary engineering skills (ABAP/BASIS) required to lead support for these systems. Additionally, the candidate lacks the strictly required Spanish language proficiency for this LATAM-focused role.

[ANALYSIS_REPORT] The candidate has a strong functional background in Supply Chain, Finance, and Project Management, which aligns with the business domain. However, the role explicitly requires 'SAP CPM' (Commercial Project Management) expertise, a specific SAP module which is not present in the resume. While the candidate is a fast learner with ERP experience, SAP consultant roles typically demand specific prior configuration knowledge.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a high-potential match with deep 'metal-up' understanding of AI infrastructure (Self-hosted LLMs) and proven experience building autonomous systems (Algorithmic Trading), which strongly correlates with the 'Agentic' requirements despite missing specific framework keywords. The 'Fast Learner' trait helps bridge the gap for tools like CrewAI or OCI. The only significant hard skill gap is the specific requirement for 'Strong JavaScript/TypeScript' for backend services, as the candidate's profile is heavily Python/Infrastructure centric.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong technical fit for the 'System Configuration', 'API integration', and 'SQL' requirements, with a proven ability to build complex logical systems (Logistics/JIT) that parallel travel booking complexities. The 'Fast Learner' trait suggests they can bridge the domain gap. However, the candidate lacks the explicitly required 'Air Travel Technology' and 'Airline Distribution' experience, which is a significant domain-specific hurdle.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong cultural and domain fit: The candidate's background in Supply Chain (Pronutri/Electrolux) and Fintech (Atlas/CryptoCall) aligns perfectly with Mottu's business. The 'hands-on', 'ownership' mentality is evident in his self-hosted ventures. However, a significant technical gap exists: the role strictly requires 5 years of Node.js/NestJS, whereas the candidate is a Python/Automation expert. While he is a 'Fast Learner' (Self-hosted LLMs, metal-up architecture), the specific framework seniority is missing.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the core Integration Developer profile. The candidate possesses the required hard skills in Python, Cloud (AWS), and advanced Authentication (OIDC/SAML maps directly to OAuth 2.0). His background as a 'Systems Integrator' building complex JIT and trading systems proves he can handle the API logic. The only significant gap is specific HubSpot ecosystem knowledge, which is easily bridgeable given his architectural seniority and fast-learning track record.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong mismatch in technical stack. Candidate is a modern stack expert (Python, AI, Cloud, Automation) while the role strictly requires legacy structured programming (COBOL/Dataflex) for reverse engineering. Excellent domain fit in Retail/Supply Chain raises the score slightly, but the core technical requirement is completely missing and not adjacent to the candidate's current expertise.

[ANALYSIS_REPORT] [Model: gemini-cli] Critical domain mismatch. The candidate is a senior Backend/Infrastructure Architect (Python, AI, Automation), while the role is a specialized Frontend Engineer position. Although the candidate's AI expertise is a 'nice-to-have' for the company, they lack the entire core technology stack required for the daily responsibilities (React ecosystem).

[ANALYSIS_REPORT] Strong cultural and technical match due to 'Founder' mindset and hands-on AI/LLM experience, which aligns perfectly with Entrupy's domain. However, the candidate's Python experience leans heavily towards Automation/Data/Systems rather than serving high-scale APIs for mobile clients. Key gaps include specific web frameworks, NoSQL databases, and deep AWS production experience (candidate lists 'Basics').

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is vastly overqualified for this position. The only strict requirement is a High School diploma, which the candidate exceeds with a Bachelor's in Mechatronics Engineering. His background in manufacturing (Pronutri), supply chain, and robotics ensures he possesses the aptitude for the operational tasks described, although the role is a significant step down from his current strategic architecture level.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate has a strong Engineering and Management background, fitting the 'Engineering' differential and leadership requirements well. As a 'Fast Learner' with a Mechatronics degree, they can likely handle the instrumentation/sensor tasks. However, the role is heavily focused on Field Operations (potentially Marine/Environmental, citing 'diving/vessels'), whereas the candidate's recent expertise is deeply specialized in Software, Cloud, and Finance. They are vastly overqualified for the IT requirements (Python/AI vs Windows/Office) but lack the specific field domain context.

[ANALYSIS_REPORT] Major role mismatch. Candidate is a Systems Engineer/Architect focused on automation and algo-trading. The role is an operational Senior Financial Analyst (AP/AR, tax compliance, bank reconciliation). While the candidate has 'Financial Analyst' experience, it was in high-level crypto risk/trading, not the administrative accounting tasks required here. He is overqualified technically (Python/SQL vs Excel) but lacks the specific operational accounting background and the requested degree.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a strong Technical Architect/Builder (Python/Infra) applying for a specialized QA/Quality Engineering role (Java/.NET). While the candidate has strong 'Fast Learner' traits and matches the Container/CI/CD requirements, the role requires specific experience in maintaining Java frameworks and performing static analysis on Java/.NET applications, which is a significant language ecosystem gap. The shift from Architecture/Trading to QA processes is also a domain leap.