[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a very strong match for the 'Software Development Engineer' aspect of the role, possessing 5/6 core technical requirements (Python, SQL, Linux, REST APIs, Networking concepts). The primary gap is specific QA tooling (Selenium) and the 'Test' domain expertise, but their background in building complex automated systems, risk management, and self-hosted infrastructure indicates a high aptitude for automation logic and rapid upskilling. The Mechatronics degree fits the 'related field' requirement.

[ANALYSIS_REPORT] [Model: gemini-cli] Significant domain mismatch. The candidate is a senior Systems Architect specializing in Python, AI, and Infrastructure, while the role strictly requires a Senior Full Stack Web Developer with 10+ years of PHP and deep CMS (WordPress/Drupal) expertise. While the candidate has transferable engineering logic and matches on Docker/Linux, the specific requirement for legacy web stack proficiency and frontend design is entirely absent.

[ANALYSIS_REPORT] [Model: gemini-cli] Major domain mismatch. The role strictly requires specific GIS software proficiency (ArcGIS, QGIS) and a Civil Engineering background (specifically asking for a current student). While the candidate's automation and Python skills align with the 'Desirable' criteria, they lack the core mandatory hard skills to perform the primary function of technical support for these specific geospatial tools.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong domain fit (FinTech, Automation, API integrations) and proven 'figure it out' engineering ability. However, this is a significant Tech Stack mismatch. The candidate is a Python/Data/Infrastructure engineer, while the role strictly requires a Node.js/React Full-Stack profile. While the candidate understands the business logic perfectly (automating financial flows), the lack of JavaScript/TypeScript and Frontend (React) experience represents a steep learning curve for immediate contribution.

[ANALYSIS_REPORT] Critical mismatch. The job is an entry-level administrative apprenticeship (likely 'Jovem Aprendiz') explicitly restricted to candidates aged 18-22. The candidate is a 33-year-old Senior Solutions Architect with 10+ years of experience, making them statistically ineligible and vastly overqualified.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is an exceptional fit for the 'Founder/Engineer' persona requested. His self-taught experience with 'Local AI Clusters' and 'LLMs' aligns perfectly with the company's AI mission. He demonstrates the exact 'Technical Bridge' capability required, connecting business logic (Supply Chain/Finance) with engineering implementation. His Python and automation depth exceeds the 'Some programming' requirement.

[ANALYSIS_REPORT] Major role mismatch. The candidate is a Senior Technical Architect/Engineer focused on AI and Automation, whereas the role is a non-technical Commercial Account Manager focused on sales, retention, and insurance policies. While the candidate has a financial background (Atlas Quantum) and general business acumen, they lack the specific 'Account Management' and 'Insurance Sales' experience required. Their technical skills (Python, Docker, Terraform) are irrelevant to this position.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate has a strong engineering foundation with Python, SQL, and AWS, backed by proven success in building complex, data-driven systems (Algorithmic Trading, JIT Inventory). While he lacks specific enterprise data platform experience (Databricks, Snowflake) typically requested for a Senior Data Engineer role, his 'Fast Learner' profile and experience with self-hosted infrastructure and complex logic suggest he can rapidly bridge these gaps.

[ANALYSIS_REPORT] Strong match on core logic and hard skills (Python, SQL, Automation, ETL/Pipelines) demonstrated through complex projects (JIT Inventory, Crypto Trading). The candidate's 'Fast Learner' trait and architectural background strongly suggest the ability to handle Data Engineering tasks despite the lack of a formal title. Core gaps are specific enterprise data tools which are likely easily learned.

[ANALYSIS_REPORT] The candidate is a technical Solutions Architect/Engineer, while the role is for a Retail Operations Manager focusing on physical store logistics and team HR management. The candidate is significantly overqualified technically (Python, AI, Automation) but lacks the specific recent experience in physical retail floor management (opening/closing stores) and direct people/HR management required for this role.

[ANALYSIS_REPORT] [Model: gemini-cli] Major domain mismatch. The candidate is a Senior Software/AI Solutions Architect, while the role is a functional Mechanical Drafting/Junior Engineering position. While the candidate's Mechatronics degree provides a theoretical foundation, their 10+ year career is dedicated to software, finance, and AI infrastructure, lacking the required recent operational experience in mechanical CAD tools and manufacturing inspection.

[ANALYSIS_REPORT] Strong match for the strategic goals of 'process implementation and automation'. The candidate's 'Head of Engineering' and 'Founder' experience effectively covers the Project and Product Management requirements, especially regarding automation and AI (a listed plus). While the specific 'Senior Project Manager' title is absent, the functional experience in optimizing supply chains and building systems exceeds the 'Business Analysis' requirements. The candidate acts as a builder-architect, which may be more valuable than a pure administrator for this specific role.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a high-caliber Engineering/Systems Architect with strong relevance to the 'AI platform' domain. However, there is a significant technology stack mismatch. The candidate is a Python/Infrastructure specialist, whereas the role requires a Senior Full Stack Developer specifically fluent in the MERN stack (React, Node, Express). The 'Frontend' domain is entirely missing from the resume.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a strong Systems Architect with relevant ERP/Supply Chain domain experience (highly desired). Their 'Fast Learner' ability is evident through self-hosted AI/LLM projects, which likely covers the conceptual AI framework requirements. However, the candidate lacks the explicitly required secondary backend language (Golang/Java/Node.js) to pair with Python and lists only 'AWS Basics' where 'Strong grounding' in cloud is required. Professional experience with Vector DBs is also absent.

[ANALYSIS_REPORT] [Model: gemini-cli] Critical role mismatch. The candidate is a Technical Solutions Architect and Engineer focused on software automation, AI infrastructure, and supply chain analytics. The position is for a Senior Talent Acquisition Partner (Human Resources), responsible for recruiting drivers and operational staff. There is no functional overlap between engineering systems and managing high-volume recruitment processes.

[ANALYSIS_REPORT] Candidate is a strong match, possessing all critical 'MUST' hard skills (Python, SQL, ETL, DevOps/MLOps) demonstrated through complex, self-driven projects (JIT inventory, algorithmic trading, self-hosted LLMs). His practical experience with Python (6+ years) and Systems Architecture exceeds the 'Intermediate' requirements. The only gaps are specific enterprise 'Data Governance' frameworks and the desirable Insurance domain knowledge, both of which are outweighed by his proven capacity to build production-grade data systems from scratch.

[ANALYSIS_REPORT] Strong match on core DevOps fundamentals (Terraform, Docker, CI/CD, Python) and the specific 'GenAI' requirement (deep local LLM experience). The candidate's background in Finance and Supply Chain makes them uniquely qualified for the 'Cloud Cost Management' requirement. However, the role strictly requires 3+ years of deep Azure expertise (AKS, Azure Monitor), whereas the candidate primarily lists AWS and local infrastructure. Given the 'Fast Learner' profile and architectural depth, they could adapt, but the lack of immediate Azure production fluency is a significant gap for a Senior role.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a high-level Solutions Architect and Engineer with strong automation and process optimization skills, but heavily misaligned with the specific requirement for a Senior SAP Test Manager. While the candidate has some ERP exposure (process improvement), they lack the mandatory deep expertise in SAP ecosystems (ECC/S/4HANA), formal Test Management (SIT/UAT) methodologies, and specific tools like SAP Solution Manager required for this senior role.

[ANALYSIS_REPORT] The candidate is a strong strategic fit, particularly for the 'process implementation and automation' and 'AI' aspects of the role. His experience as a Founder and Architect demonstrates high-level Project Management and Business Analysis capabilities (e.g., designing JIT systems, optimizing workflows). He exceeds the 'AI implementation' preference. The primary gap is the lack of specific 'Project Manager' or 'Product Manager' job titles for the requested 3-4+ year duration, though his functional experience covers these requirements.

[ANALYSIS_REPORT] Candidate is a strong technical match with confirmed expertise in Python, SQL, and quantitative risk analysis (Crypto/Finance). The 'Fast Learner' trait is highly demonstrated through self-hosted AI clusters and automated JIT systems, indicating they can rapidly master the specific BI tools required. The significant gap is the specific domain expertise in Card-Present/Card-Not-Present payments fraud, but their experience with algorithmic risk management serves as a strong parallel foundation.

[ANALYSIS_REPORT] Significant role mismatch. The candidate is a Senior Systems Architect and Engineer, whereas the position is a Commercial/Operational role focused on Tourism Product Management and Franchise relations. While the candidate possesses superior analytical skills and AI knowledge (exceeding the 'ChatGPT' requirement), they lack the specific tourism industry experience and sales background required. Their engineering talent would be underutilized.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate excels in Python automation and the specific AI/LLM domain required, demonstrating strong 'Fast Learner' traits (self-hosted clusters). However, the role is explicitly 'Full Stack' with heavy emphasis on Frontend (React/TS) and commercial Web Backend (Django) development. The candidate effectively misses the entire Frontend domain and the specific web-framework flavor of Python required for a SaaS platform.

[ANALYSIS_REPORT] [Model: gemini-cli] Major role mismatch. The candidate is a Senior Solutions Architect with 10+ years in Software, AI, and Supply Chain automation. The job appears to be a Regulatory/Certification Analyst role (likely junior/mid-level given 'Superior cursando') focused specifically on the bureaucracy of certifying electromedical devices. While the candidate's Mechatronics degree is relevant to the *product*, the resume lacks the specific regulatory compliance experience required for the role.

[ANALYSIS_REPORT] [Model: gemini-cli] Critical mismatch in domain and career stage. The candidate is a Senior Solutions Architect/Founder with over 10 years of experience, whereas the role is an entry-level Internship in Human Resources. Crucially, the candidate lacks the mandatory 'Active Student Status' in Psychology, Administration, or HR required for an internship contract. While overqualified for the administrative tasks, the specific domain (Recruitment & Selection) is completely absent from his technical background.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate is a strong Backend/Systems Architect (Python, AI, Automation) but the role is strictly for a Front End Engineer. There is a complete domain mismatch; the resume lacks any mention of ReactJS, JavaScript, HTML, or CSS, which are the core requirements.

[ANALYSIS_REPORT] [Model: gemini-vertex] Candidate is technically overqualified for a 'Junior' role regarding Backend (Python), Infrastructure (Terraform/Docker), and System Architecture. Strong Engineering foundation (Mechatronics) aligns with the Math/Physics requirement. The primary gap is the 'Full Stack' requirement, specifically Modern Frontend Frameworks, which are absent from the resume. Given the 'Fast Learner' context (self-hosting LLMs, Algo Trading), the candidate is highly likely to close the Frontend gap quickly.

[ANALYSIS_REPORT] The candidate matches the core educational (Engineering) and analytical requirements (Financial Analysis, Advanced English). His proficiency in Python/Pandas for data analysis far exceeds the 'Intermediate Excel' requirement, demonstrating superior analytical capability. The primary gaps are domain-specific to Real Estate (specific ABNT norms, zoning laws, and property valuation methods), but his background in Mechatronics and quantitative finance suggests these rules-based frameworks would be rapidly acquired.

[ANALYSIS_REPORT] Critical role mismatch. The candidate is a Solutions Architect focused on AI and Engineering, while the position is a Commercial Wealth Management role. The candidate lacks the strictly mandatory regulatory certification (CEA) and the specific sales/advisory experience required for high-net-worth banking, despite previous financial market exposure.

[ANALYSIS_REPORT] Critical mismatch. The candidate is legally ineligible for this position. The role is a 'Young Apprentice' program specifically restricting candidates to ages 14-24, whereas the candidate is 33. Furthermore, the candidate is a Senior Solutions Architect with 10+ years of experience, vastly overqualifying them for this entry-level administrative support role which requires no experience.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate is a strong fit for the architectural and engineering requirements, particularly given the 'Fast Learner' context. His experience with Python, automation, and 'metal-up' infrastructure (Docker, Terraform, Local Clusters) translates well to designing log management systems. He meets the degree and programming language requirements. The primary gap is specific commercial experience with 'Large Scale' distributed systems (Big Data scale vs. his complex but likely smaller-scale self-hosted/SMB systems) and his self-assessed 'Basic' AWS level versus the 'Experience' desired.

[ANALYSIS_REPORT] The candidate is overqualified in technical domains (AI, Python, Cloud) for this operational role but possesses the foundational Engineering education (Mechatronics) and Procurement background required. The primary gap is specific domain knowledge of the automotive maintenance market (parts, labor costs, workshop networks), as his recent experience is in Finance/Tech and previous procurement was in Foodservice/Appliances.

[ANALYSIS_REPORT] Severe Role Mismatch. The candidate is a Senior Solutions Architect and Software Engineer focusing on high-level automation, AI, and cloud infrastructure. The job description is a talent bank entry specifically targeting 'Machine and Equipment Operators' (manual/operational roles in industrial or agricultural contexts). While the candidate's Mechatronics degree provides theoretical knowledge, the role requires practical operational execution (blue-collar) rather than engineering strategy (white-collar).

[ANALYSIS_REPORT] [Model: gemini-vertex] High value match on the niche 'AI Agents' and 'Applied AI' requirements, where the candidate has proven, hands-on experience with self-hosted LLMs and complex system architecture. However, there is a significant mismatch in the core development stack: the role is a Fullstack position requiring strong JavaScript/TypeScript and Frontend (React/Vue) experience, while the candidate is a Python/Infrastructure specialist. While 'Fast Learner' traits suggest he could adapt to GCP and MongoDB quickly, the lack of modern Frontend/JS ecosystem experience is a notable gap for a Mid-level Fullstack role.

[ANALYSIS_REPORT] [Model: gemini-vertex] Fundamental domain mismatch. The candidate is a highly skilled Backend/Infrastructure/Data engineer with strong automation and Python experience, but the role is strictly for a Frontend Developer specializing in React.js. While the candidate has CI/CD and Git experience, they lack the core required frontend stack.

[ANALYSIS_REPORT] [Model: gemini-vertex] Significant domain mismatch. The candidate is a highly capable Backend/Systems Architect (Python, Infrastructure, AI) applying for a specialized Frontend Engineering role. While the candidate's 'Fast Learner' trait is acknowledged, there is zero evidence of the core required stack (Web UI, JavaScript, CSS) in the resume. This falls under the 'totally missing domain' penalty.

[ANALYSIS_REPORT] [Model: gemini-vertex] Critical domain mismatch. The candidate is a Senior Systems Architect and Engineer applying for a non-technical Recruitment/HR role. While the candidate meets the language requirements (Portuguese/English) and exceeds the general analytical requirements (Excel/Math), they completely lack the core hard skills and experience in recruitment, market research, and the specific healthcare domain required for this position.

[ANALYSIS_REPORT] Major technical mismatch despite strong mission alignment. The role is explicitly for a Frontend/Full-Stack Engineer (React/TypeScript, UI/UX focus), whereas the candidate is a Backend/Infrastructure specialist (Python, SQL, DevOps). While the candidate's experience with AI agents and self-hosted LLMs is a perfect match for the company's domain ('Preferred' section), they lack the core hard skills required to build the 'high-fidelity web apps' described in the primary responsibilities.

[ANALYSIS_REPORT] The candidate matches the foundational requirements (Python, Docker, AI/LLM familiarity, Engineering background) and demonstrates the 'Fast Learner' trait via self-hosted AI clusters. However, the role is heavily specialized in *Offensive Security* and *Red Teaming*, which is a distinct domain from the candidate's *Systems Architecture* and *Integrator* focus. While the candidate understands the *target* (LLMs), the specific tradecraft of exploitation and reverse engineering represents a significant skill gap.

[ANALYSIS_REPORT] Critical domain mismatch. The role is a Human Resources position (HRBP/Generalist) focusing on people management, recruitment, and organizational culture. The candidate is a Solutions Architect and Engineer with expertise in AI, IT infrastructure, and Supply Chain. While the candidate is highly skilled tech-wise, they lack the specific HR domain experience required for this role.

[ANALYSIS_REPORT] Strong match for the 'AI-powered solutions' and 'Customer Facing' aspects. The candidate's background in building autonomous systems (JIT inventory, Trading Bots) aligns perfectly with the goal of 'integrating automation' and 'agentic' workflows. While the resume lacks explicit commercial 'SaaS' team experience and specific 'Django' web framework years (listing Python Automation instead), the 'Fast Learner' trait and deep experience with self-hosted LLMs/Python logic suggests he can bridge the framework gap rapidly. He is effectively doing 'Agentic' work without the specific library keywords.

[ANALYSIS_REPORT] Strong alignment on AI/ML architecture, Python, and complex backend systems. The candidate's 'metal-up' approach and self-hosted AI cluster experience validate the 'Fast Learner' and 'AI/ML Engineer' requirements (2+ years). However, the role explicitly targets a 'Full Stack Developer' with Frontend (React) and Node.js ecosystems. The candidate is a Backend/Infrastructure specialist with no listed Frontend experience, representing a missing domain.

[ANALYSIS_REPORT] Strong domain fit: The candidate has deep experience in Supply Chain, Procurement, and Finance (the business logic of ERPs) and solid technical skills for integrations (APIs, Python, SQL). However, the role explicitly requires 3+ years of specific 'Sage ERP' configuration experience, which is missing. He would need to learn the specific tool interface, though his underlying knowledge of ERP logic is excellent.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate has excellent underlying business domain knowledge (Supply Chain, Finance, OTC processes) and strong general engineering skills (Python, Automation). However, the role is explicitly for an SAP Functional Consultant requiring specific configuration experience in SAP SD and FI modules. The candidate's resume shows custom development and general ERP improvement experience, but lacks the specific proprietary SAP ecosystem skills (Configuration, ABAP, S/4HANA) required to perform the core duties immediately.

[ANALYSIS_REPORT] Critical Domain Mismatch. The Job Description is specifically for a talent pool of 'Machine and Equipment Operators' (operational/blue-collar roles) within the agribusiness sector. The candidate is a Senior Solutions Architect and Software Engineer with a focus on AI and Cloud Infrastructure. Despite a background in Mechatronics, the candidate's career is firmly established in high-level technology strategy and development, not industrial machine operation.

[ANALYSIS_REPORT] [Model: gemini-vertex] Strong match on core requirements: Python, System Architecture, and hands-on GenAI experience (self-hosted LLMs). The candidate's 'Fast Learner' trait is evident through complex self-built systems (JIT inventory, Algo Trading). Primary gaps are in specific Enterprise-grade orchestration and data tools (Kubernetes/OpenShift, Kafka) required for this Senior role. While he has container experience (Docker), the specific orchestration and streaming stack is missing, though highly learnable given his background.

[ANALYSIS_REPORT] [Model: gemini-vertex] Strong cultural alignment with the 'Founder mindset' and 'Business impact' requirements, plus excellent match on 'AI Fluency' and infrastructure. However, the candidate is a Python/Data/Backend specialist, whereas the role strictly requires a Senior Full-Stack Engineer with 5+ years in the JavaScript ecosystem (React/Node/TS). While a fast learner, the lack of demonstrated Frontend/Web UI experience represents a missing domain.

[ANALYSIS_REPORT] Candidate is a high-potential match who operates as a 'systems builder' rather than a traditional title-focused Data Engineer. Their experience building autonomous JIT engines and algorithmic trading bots demonstrates mastery of the core job requirements: complex data pipelines, automation, and business logic implementation using Python and SQL. The primary gaps are specific 'Modern Data Stack' ecosystem tools (dbt, Airflow), but their proficiency with Terraform, Docker, and self-hosted infrastructure suggests they can master these specific implementations rapidly. They fit the 'Founding Engineer' archetype well.

[ANALYSIS_REPORT] Excellent match. The candidate hits the 'bonus' Python requirement as a core strength and possesses the specific mix of Data Engineering (Pandas/NumPy), DevOps (Terraform/Docker/CI/CD), and Algorithmic logic (Trading bots) requested. The niche requirement for 'Parallel computing' is well-evidenced by the 'Local AI/GPU Cluster' experience. The only potential gap is specific experience with C# (listed as an alternative to Python) and explicit high-scale REST API construction vs. integration.

[ANALYSIS_REPORT] The candidate is a Python/Cloud Solutions Architect with absolutely no experience in the SAP ecosystem. This is a specialized Senior Developer role requiring 5+ years of ABAP and Fiori, which are proprietary technologies distinct from the candidate's stack (Python/Docker/AI). Domain knowledge in Supply Chain exists, but the technical mismatch is total.

[ANALYSIS_REPORT] [Model: gemini-vertex] Critical domain mismatch. The role specifically requires 7+ years of deep Salesforce platform expertise (Apex, LWC, Sales Cloud), whereas the candidate is a Python/AI Systems Architect. While a fast learner in infrastructure/backend, the specialized nature of a Senior Salesforce role makes this a non-transferable match without significant retraining.