[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.

[ANALYSIS_REPORT] [Model: gemini-vertex] Critical domain mismatch. The role specifically seeks an 'Expert-level Java Specialist', whereas the candidate is a Python/Systems Architect. While the candidate's DevOps and AI/LLM experience is a 'Strong Plus' per the JD, the complete absence of the primary required stack (Java, Spring Boot, React, Node.js) makes them unqualified for this specific specialist seat.

[ANALYSIS_REPORT] Strong match for the analytical and integration requirements. The candidate's background in 'Systems Integration' and 'Python/Pandas Automation' effectively covers the 'ETL' and 'API' needs, even if specific legacy tools (Pentaho/SSIS) are not listed. His experience with 'Supply Chain Analytics' and 'Financial Logic' aligns perfectly with the role's need for business logic translation. The primary gap is specific legacy SQL administration (Triggers/Procedures) and Salesforce, but his technical depth suggests these would be trivial to pick up.

[ANALYSIS_REPORT] [Model: gemini-vertex] Candidate is a strong Systems/Backend engineer with proven 'Fast Learner' traits (Quant, Self-hosting LLMs). While he lacks the specific requested language (Go) and orchestration tool (Kubernetes), his deep experience in Python, SQL, and Docker demonstrates transferrable backend fundamentals. He fits the 'Systems' aspect well but will need a ramp-up period for Go syntax and Kubernetes-specific workflows.

[ANALYSIS_REPORT] [Model: gemini-vertex] Critical mismatch in core technology. The role requires a Senior SAP Specialist to manage specific SAP support contracts (AMS) and vendors. While the candidate has strong domain knowledge in Supply Chain and Finance (matching the business side of SAP MM/FI), and general procurement experience, they lack the strictly required SAP ecosystem experience (ECC, S/4 Hana) and specific IT Service Management background.

[ANALYSIS_REPORT] Candidate meets and exceeds the 6-year Python requirement (active since 2018 in algorithmic trading and automation). Possesses required AWS exposure ('AWS Basics'). While 'PySpark' is not explicitly listed, the candidate's strong proficiency in Pandas, NumPy, and SQL, combined with a proven ability to build complex self-hosted systems (Fast Learner), suggests a very low barrier to entry for distributed data processing.

[ANALYSIS_REPORT] The candidate has strong Domain relevance (Fintech/Trading) and demonstrates Architectural capability. However, this is a Tech Lead role specifically requiring **Java** and **Golang** expertise to mentor a team, whereas the candidate is a **Python** specialist. While the candidate is a fast learner, the gap in the core technology stack and the lack of explicit corporate people management experience (PDIs, 1:1s) significantly impacts the match for a leadership position.

[ANALYSIS_REPORT] [Model: gemini-vertex] Strong cultural fit for SRE (focus on automation, self-healing systems, and 'zero maintenance'). Excellent Python and Terraform foundations. However, significant gaps exist in specific required platforms (GCP, Azure) and orchestration (Kubernetes), though the candidate's 'metal-up' experience with local AI clusters suggests high aptitude to bridge these gaps quickly.

[ANALYSIS_REPORT] Strong domain fit in Supply Chain, Finance, and ERP logic (Procurement/Inventory), plus proven API integration skills. However, this is a platform-specific role requiring 3+ years of Acumatica and C#/.NET, while the candidate is Python/Linux focused. Significant upskilling required for the specific tool and language.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate has strong foundational alignment in DevOps principles (CI/CD, Docker, Automation, Python) and a proven ability to architect complex systems (Fast Learner). However, this is a 'Tool Specialist' role focused on the Java/CloudBees ecosystem. While the candidate can likely learn the tools (Jenkins, Ansible) quickly given their Terraform/Scripting background, the requirement for practical development experience in Java/Maven or C++ represents a distinct stack gap compared to their Python/Systems focus.

[ANALYSIS_REPORT] [Model: gemini-vertex] Significant role mismatch. The position is for a Senior Project/Agile Process Analyst focused on governance, coaching, and specific frameworks (SAFe, ITIL, Scrum). The candidate is a technical Solutions Architect and Engineer focused on building, automation, and infrastructure. While the candidate has operational management experience (Supply Chain), they lack the specific formal Agile/Project Management certifications and framework expertise required.

[ANALYSIS_REPORT] Excellent fit. The candidate's profile explicitly defines them as a 'Technical Bridge', which matches the core 'Solutions Engineer' requirement of connecting business goals with engineering. The candidate possesses the required Python, API, and System Design skills with over 6 years of relevant experience. The primary gaps are domain-specific (AdTech) and specific experience with 'Big Data' at the enterprise scale, though the algorithmic trading background serves as a strong proxy.

[ANALYSIS_REPORT] Critical eligibility mismatch: The role is strictly for current students graduating 2026-2027 (Internship), whereas the candidate is a senior professional with 10+ years of experience (graduated 2014). Additionally, the role focuses on User Research/UX, while the candidate is an AI/Systems Architect.

[ANALYSIS_REPORT] Critical disqualifier: The role explicitly requires business fluency in German, which is not listed on the resume. Additionally, this is a 'Project Assistant' role focused on administrative coordination and qualitative recruitment, whereas the candidate is a senior-level Solutions Architect and Head of Engineering. The candidate is vastly overqualified and lacks the specific qualitative healthcare research focus.

[ANALYSIS_REPORT] Candidate demonstrates exceptional 'metal-up' understanding of AI infrastructure (Self-hosted LLMs, GPU clusters) and complex system automation (JIT engines), aligning well with the 'Fast Learner' and 'Builder' profiles. The score is docked primarily due to the lack of specific enterprise AI stack keywords (RAG, Vector DBs, Fine-tuning) and the disparity between 'AWS Basics' and the requirement for 'Scalable/Distributed Cloud Systems'. However, his background suggests he can bridge these gaps rapidly.

[ANALYSIS_REPORT] [Model: gemini-vertex] Major domain mismatch. The candidate is a high-level Systems Architect and Software Engineer, while the role is strictly for Automotive Regulatory Compliance (Homologation). Although the candidate possesses the required Engineering degree and English fluency, they lack the specific, non-negotiable experience with Brazilian government vehicle certification systems (INFOSERV/SISCAT) and emissions/safety testing standards required by the job.

[ANALYSIS_REPORT] [Model: gemini-vertex] Major technical stack mismatch. The candidate is a senior Python/Infrastructure/AI Architect, while the role strictly requires a PHP Web Developer with frontend skills (HTML/CSS/JS) and Windows Server experience. While the candidate is a 'Fast Learner' with strong backend logic and API experience, the core daily tools (PHP, Legacy Web) are completely absent from the resume.

[ANALYSIS_REPORT] Significant domain mismatch. The candidate is a high-level Solutions Architect and Automation Engineer, while this role is a non-technical Commercial/Account Management position specifically requiring airline industry experience. While the candidate's analytical skills (Python/Pandas) vastly exceed the requirement (Intermediate Excel), the core mandate for 'Commercial experience in the airline segment' and Spanish language proficiency are critical missing hard skills.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate is a strong technical fit for the 'Backend' and 'Data' verticals of this talent pool, reinforced by relevant domain experience in Supply Chain/Logistics (Syngenta context). The candidate meets the innovation and self-learning requirements. However, this is an Affirmative Action (Diversity) listing; as a Male candidate, eligibility depends on unstated diversity criteria (e.g., ethnicity, PwD). He lacks the Mobile/Frontend skills mentioned as part of the wider pool scope.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate is a high-potential Systems Architect with strong data engineering fundamentals (Python, ETL logic, CI/CD) and a proven 'fast learner' ability (Local LLMs, Algo Trading). However, the role is strictly a Snowflake & Azure specialist position requiring 'proven practical experience'. While the candidate can undoubtedly learn the stack rapidly, they lack the specific hard skills (Snowflake, ADF) required for immediate impact in this senior-level role.

[ANALYSIS_REPORT] The candidate has strong foundational coding (Python, SQL) and system automation skills (JIT engines, API integration), demonstrating the 'Fast Learner' trait. However, this is a Senior Data Engineering role heavily dependent on the Azure ecosystem (Data Factory, Databricks, Synapse) and specific Big Data orchestration tools (AWS Glue, Airflow) which are completely absent from the resume. While the candidate understands data logic, the specific enterprise stack gap is significant for a Senior-level position.

[ANALYSIS_REPORT] The candidate is a high-level Systems Architect with exceptional automation and programming skills (Python, CI/CD, APIs), which are a 'Big Plus' for this role. However, there is a significant domain gap: he lacks the required 3-4 years of formal 'QA Engineer' experience, the ISTQB certification, and specific mention of standard testing frameworks (e.g., Selenium, Cypress) or UI testing. While his 'Fast Learner' trait suggests he could adapt quickly, he is currently a 'Builder' rather than a 'Tester' on paper.

[ANALYSIS_REPORT] [Model: gemini-vertex] The candidate is a capable Python-based Systems/Automation Engineer, but the role is strictly for a .NET Backend Developer. While the domain (Backend) matches, the core technology stack (.NET ecosystem) is completely missing. The candidate's experience focuses on self-hosted automation and scripting rather than the specific enterprise patterns requested (Microservices, Hexagonal Architecture). Despite 'Fast Learner' traits, the gap between Python automation and Enterprise .NET Microservices is significant for a senior/mid-level role.

[ANALYSIS_REPORT] [Model: gemini-vertex] Strong foundational match in Python, data automation, and general infrastructure (Terraform, CI/CD, SQL). However, the role is a specific 'Azure Data Engineer' position requiring the Azure data stack (Data Factory, Databricks, Synapse) and distributed processing (Spark), whereas the candidate's experience is focused on Python-based local/AWS automation and single-node data processing (Pandas). While a 'Fast Learner' capable of bridging the gap, the specific cloud ecosystem experience is currently missing.