[ANALYSIS_REPORT] [Model: gemini-cli] The candidate significantly exceeds the technical baseline for this Junior (IC1) role. Their background in 'Systems Engineering', 'Terraform', 'Python', and 'Local AI Clusters' aligns perfectly with the JD's focus on Automation, Infrastructure, and AIOps. The candidate's specific experience self-hosting LLMs is a high-value match for the 'AIOps' requirement. Primary gaps are platform-specific (OCI) and orchestration-specific (Kubernetes), but given the 'Fast Learner' profile and Docker proficiency, these are trivial bridges.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong domain fit: The candidate's background in Supply Chain/Logistics and 'JIT inventory systems' aligns perfectly with the 'Nice-to-have' TMS focus, often harder to find than tech skills. Architecture and 'reverse engineering' mindset (crypto bots, custom APIs) are present. Main deductions are for the specific tech stack: the role strictly requires Go (Golang) and browser automation tools (Selenium/Playwright), whereas the candidate is heavily Python-focused. Given the 'Fast Learner' profile (self-hosted LLMs), the language gap is bridgeable.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong technical match. Candidate possesses core requirement trinity: Python, SQL, and Infrastructure (Docker/Terraform/AWS). Experience building 'end-to-end logistics logic' and 'JIT inventory engines' maps directly to the required ETL/Data Pipeline tasks. 'Fast Learner' context (self-hosted LLMs, algorithmic trading) strongly mitigates the lack of specific 'Big Data' tool keywords. Main gap is the specific 'Enterprise Data Engineering' job title history versus his 'Systems/Solutions' background, and specific API protocols.

[ANALYSIS_REPORT] [Model: gemini-cli] Major role mismatch. The candidate is a high-level Solutions Architect/DevOps Engineer (Linux, Python, AI, Automation) while the job is a traditional Corporate SysAdmin/NetSec role (Microsoft, Cisco, Firewalls, Support). While the candidate is technically capable of learning, they currently lack the specific ecosystem experience (Windows Server, Active Directory, Cisco/Fortinet hardware) required for day-one operations.

[ANALYSIS_REPORT] [Model: gemini-cli] Significant role and seniority mismatch. The candidate is a Senior Systems Architect/Engineer focused on automating operations and AI infrastructure, whereas the role is an administrative assistant position focused on manual process execution (checking photos, updating reports). While the candidate is technically capable of performing these tasks, the role ignores their engineering expertise and represents a career regression from 'Head of Engineering' to 'Project Assistant'.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a highly technical Engineering/Operations manager, whereas the role demands a Marketing/Events Project Manager. While the candidate possesses strong general project management capabilities (planning, timelines, execution), they completely lack the required domain expertise in Digital Launches, Marketing Campaigns, and Corporate Events. The mismatch between an Engineering Architect and a Marketing PM is significant.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate acts as a strong 'Technical Bridge' (Atlas Quantum) with deep experience translating business logic into technical execution (Founder/Supply Chain). Excellent match for the logic/API/integration aspects. However, the resume lacks the specific formal documentation methodology keywords (BPMN, UML, User Stories) and management tools (Jira/Confluence) required for a dedicated Senior Analyst role, though these are easily learnable for an experienced engineer.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate demonstrates exceptional process ownership and automation capability ('Dono do processo', JIT systems), aligning well with the soft skill requirements. However, there is a critical technical mismatch: the role strictly requires 'Microsoft 365/Google Workspace Migration' and corporate IT governance (ITIL, AD), while the candidate's expertise is in Linux, Python, and AI/DevOps architecture. He is likely overqualified for the Service Desk components but lacks the specific Microsoft ecosystem experience requested.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for a Python-centric Backend role. Candidate exceeds the 5+ years Python requirement (active since ~2018 in Quant/Automation roles) and meets the specific location requirement (Brazil). Core backend concepts (SQL, APIs, CI/CD, Cloud/AWS) are present. Missing skills like NoSQL and TDD are process-oriented and easily bridged given the candidate's demonstrated ability to architect complex, self-hosted AI and inventory systems.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the 'Platform' and 'Engineering' aspects of the role. The candidate excels in Python automation, Infrastructure-as-Code (Terraform), and system architecture (AWS/Docker), which meets the core requirement of building robust data platforms. The primary gaps are in specific distributed Big Data frameworks (Spark/Hive) and formal orchestration tools (Airflow), as the candidate's experience focuses on vertical scaling (Pandas/Local Clusters) rather than distributed horizontal scaling. Given his 'Fast Learner' profile and background in complex financial/supply chain data, these tool-specific gaps are likely easily bridgeable.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the 'Pleno' (Mid-Level) seniority due to robust engineering background and demonstrated ability to build complex, self-healing systems (JIT inventory, Local AI). The candidate possesses the core 'SRE Mindset' (Automation, IaC/Terraform, Scripting). The primary gaps are specific enterprise-standard tools (Kubernetes, Observability stacks) vs. his proven custom/local infrastructure experience. Given the 'Fast Learner' profile, bridging the gap from Docker/Local Clusters to Kubernetes is highly probable.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a high-potential senior engineer (Python/Infra focus) but completely lacks the mandatory core technology stack (C#/.NET) required for this specific technical leadership role. While the 'Fast Learner' trait and financial background are strong positives, the requirement to 'support the team in .NET development' makes the lack of C# experience a critical gap.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong mismatch in core domain focus. The candidate is a modern Solutions Architect/DevOps Builder (Python, Docker, Automation, AI) applying for a traditional Enterprise IT Operations/Service Management role (ITIL, Windows Server, SLAs, Support). While the candidate is 'overqualified' in engineering/logic and can easily learn the tools (Fast Learner), they lack the specific legacy administrative experience (Windows Server, Vcenter, Enterprise Networking) and the formal service management framework (ITIL) central to this role's daily duties.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is an excellent fit, likely exceeding technical requirements. Deep experience in custom Python automation and 'metal-up' AI infrastructure serves as a strong foundation to instantly master requested low-code tools (n8n, Zapier). Financial domain experience (CryptoCall, Atlas Quantum) aligns perfectly with the 'Renda Fixa/Variável' operational context.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong analytical and technical match, exceeding expectations for 'Automation' and 'Analytical Skills' (Python/Pandas experience). His 'Systems Integrator' and 'Founder' background aligns well with the 'Enterprise Implementation' and 'Protagonist of Growth' requirements. The only distinct hard skill gap is the 'Desirable' Spanish language proficiency.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match on domain (Fintech/Algo Trading) and core backend logic (Python, Pandas, Cloud, Security). However, this is a 'Data Visualization' role and the candidate completely lacks the required Front-end stack (JavaScript, HTML, CSS) and specific Big Data orchestration tools (Kafka, Spark, Airflow), positioning them more as a Systems/Backend Architect than the requested Visualization Engineer.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the 'Analytics Engineer' profile, particularly the 'bridge' aspect between business logic and technical implementation. The candidate's background in building end-to-end automation (JIT systems, Trading Bots) directly translates to the required Data Pipeline and Python capabilities. While specific 'Big Data' framework experience is implicit rather than explicit, the 'Fast Learner' trait (self-hosting LLMs/Clusters) strongly suggests capability to adapt to Nubank's specific scale. The primary gaps are specific visualization tools and explicit Data Warehouse architecture terminology.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match in core domain (Finance/Trading/Algo) and technical architecture (Backend, Python, Infra). The candidate's 'Founder' and 'Self-hosted AI' background demonstrates the required 'Fast Learner' and 'System Vision' traits. Major gap is the specific 'Solid experience with people management' in a corporate engineering context (hiring, career development, 1:1s), as the resume focuses more on technical architecture and independent consulting.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match. Candidate's background in Engineering (Mechatronics) and Supply Chain (MITx) aligns perfectly with the operational logic required for Highway/Toll systems. While lacking specific 'Project Manager' titles for 4 years, his role as 'Head of Operations' and 'Planner' demonstrates extensive practical project management, risk control, and JIT/Kanban execution. Missing tools (Jira, MS Project) are trivial gaps for a candidate capable of building automated Python pipelines and self-hosting LLMs.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate has a strong foundation in Python, Data Analysis, and Automation, reinforced by an Engineering background and 'Fast Learner' traits (self-hosted systems). However, this role is a hybrid of BI, Web Development, and Engineering Design Support. The candidate lacks the specific mandatory frontend skills (JS/HTML) and extensive experience with required proprietary industrial software (Spotfire, Primavera, E3D/Piping modeling) defined in the scope.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is highly qualified, likely exceeding the 'Junior' level. Deep practical experience with LLMs (self-hosting/optimizing) and Python automation strongly covers the core 'AI & Automations' needs. While the resume focuses on 'High-code' (Python/Shell) and local hardware, the transition to No-code tools and Azure Cloud services would be trivial for this profile given the 'Fast Learner' context.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a high-potential Systems Architect with proven 'Fast Learner' traits (self-hosted LLMs, complex automation), fitting the 'Senior' and 'High-ownership' criteria well. However, there is a significant stack mismatch: the role requires 'Advanced Node.js' (candidate is Python-focused) and 'Strong AWS' (candidate lists 'AWS Basics'). While his Terraform and SQL experience allows for rapid upskilling, he currently lacks the specific NoSQL and deep AWS expertise required to lead those specific domains immediately.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a highly technical Systems Architect/Engineer with strong capability to fulfill the Systems Analyst role. His experience in 'connecting business goals to technical infrastructure' and building systems 'from concept to execution' covers the core requirements of requirements gathering and prototyping. While he lacks specific legacy keywords like 'Oracle' or formal 'User Stories'/'Scrum' certifications, his background in Python, Automation, and JIT/Supply Chain logic proves he possesses the underlying data modeling and logic skills. He is likely overqualified technically but may need to adapt to the specific bureaucratic/methodological processes (Agile ceremonies, formal documentation) of this role.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong potential. The candidate is a high-level fit due to deep experience in Python automation, system architecture ('metal-up'), and 'Fast Learner' traits (self-hosted LLMs). He directly hits the 'LLM' and 'RAG' differentiators. However, he lacks the specific 'Modern Data Stack' tooling required (GCP, dbt, Airflow), though his experience with CI/CD and AWS suggests rapid upskilling capability. Missing explicit SQL mention is a minor gap given his Data/Pandas background.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong fit for the core 'Business Systems Analyst' requirement of bridging technology and business, evidenced by his experience at Atlas Quantum translating financial logic for engineering teams. His technical background (Python, Systems Architecture) exceeds the role's requirements, suggesting he can handle the technical validation and logic mapping with ease. The only significant gaps are the specific NoSQL database (MongoDB) and formal Agile acronyms (DOR/DOD), but his 'Fast Learner' profile and founder experience suggest he can adapt to these specific tools and workflows immediately.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match on core infrastructure (Terraform, Docker), CI/CD, and practical GenAI application (self-hosting LLMs, local clusters). The candidate demonstrates the high-level 'Figure it out' ability required for complex systems. The primary gap is specific experience with the Microsoft Azure ecosystem (JD demands deep Azure knowledge), but the candidate's background in AWS and bare-metal AI suggests a rapid transition is possible.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match. The candidate's 'metal-up' architectural background and proven 'Fast Learner' ability (self-hosted LLMs, crypto bots) align perfectly with the JD's emphasis on a 'learning-first approach' and 'troubleshooting'. While the candidate lacks specific enterprise Ops tools (DataDog, PagerDuty) and JVM languages (Java/Kotlin), their core engineering stack (Python, Docker, Terraform, Shell) is robust. The JD explicitly states 'Don’t worry if you haven’t used them all before', making the candidate's deep technical aptitude more valuable than specific tool familiarity.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong architectural and leadership profile with proven 'fast learner' capabilities in complex domains (AI/Infrastructure). However, this is a significant mismatch for a 'Technical Lead' role which specifically requires mentoring and code review in a .NET/React stack. The candidate is deeply specialized in Python/Data/Automation. While the 'Backend' and 'Cloud' domains overlap conceptually, the lack of specific stack experience (.NET, React) makes immediate technical leadership in this specific environment difficult.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for Domain (SCM/Warehouse) and Education (Engineering + MITx). The candidate's 'Founder' experience demonstrates practical project execution and ROI focus, covering the core of the role. The primary gap is the lack of explicit, formal corporate Project Management keywords (e.g., PMBOK, Agile, MS Project) which are often standard in large enterprise environments, but the candidate's technical and operational background suggests rapid adaptability.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate significantly exceeds the requirements for this entry-level Software Engineering role. The job description requests foundational knowledge of programming concepts, software design, and the ability to learn under supervision. The candidate's background as a Solutions Architect and Founder, with proven experience building production-grade JIT systems, algorithmic trading bots, and AI infrastructure, demonstrates mastery well beyond the foundational level requested.

[ANALYSIS_REPORT] [Model: gemini-cli] Severe mismatch in role function and industry domain. The candidate is a Senior Technical Architect and Engineer (Builder), whereas the position is a Project Manager in a Digital Marketing Agency (Manager/Coordinator). While the candidate has general business acumen (budgets/scopes) as a Founder, they lack the specific 'Advertising/Marketing Agency' experience explicitly required (3+ years). Their toolset (Python, Docker, Terraform) is engineering-centric, not PM-centric (MS Project, Smartsheet).

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match in Python, Financial/Supply Chain domain, and general infrastructure (Docker/Terraform). The candidate's 'metal-up' and self-hosted AI experience demonstrates high 'figure-it-out' aptitude relevant to data architecture. However, for a Senior/Principal Data Engineer role, the explicit lack of 'Big Data' framework experience (Spark, Modern Cloud DWs, Orchestrators) is a significant gap, though likely bridgeable given the candidate's backend/automation strength.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong architectural and '0-1' founder alignment. The candidate's experience in self-hosting LLMs and building complex automated systems (JIT, Trading) demonstrates the required 'figure it out' capability. Major gaps are specific AI application techniques (RAG, Vector DBs) vs. his Infrastructure focus, and a lack of explicit Frontend/Web Application frameworks, though the latter is mitigated by the 'Bubble' (no-code) option.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is significantly overqualified for this Entry Level Software Engineering role. The job description asks for 'foundational understanding' of programming and design principles, which the candidate vastly exceeds with over 10 years of experience as a Founder, Solutions Architect, and Systems Engineer building production-grade automation and AI infrastructure.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a highly technical Solutions Architect and Engineer, whereas the role is a functional implementation specialist. The candidate lacks the strictly required 'Salesforce' experience (specifically requested 'in the last 2 years'). While the candidate has strong systems integration and analytics skills, their profile is over-engineered (Python, AI, Docker) for a role focused on CRM configuration and user training.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a strong applied Solutions Architect with relevant AI hardware/infrastructure experience (local clusters, LLMs). However, this is a Research role explicitly requiring a Ph.D./MS and a history of academic publishing, which marks a significant domain gap from the candidate's applied engineering/business background. C++ is a missing hard skill.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong foundational match on core SRE/Engineering skills (Terraform, Python, Automation, CI/CD) and 'FinOps' mindset (Finance/ROI background). The candidate is a proven high-velocity learner (Self-hosted LLMs, Quant Trading), suggesting he can bridge the Cloud provider gap quickly. However, the role is highly specialized in the Azure Data Ecosystem (Databricks, Synapse, Unity Catalog), whereas the candidate's cloud experience is limited to basic AWS and local infrastructure. He fits the 'SRE' profile but lacks the specific 'Azure Data' toolset.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a highly experienced engineer (10y+) with strong domain alignment (Finance/Logic) and meets all 'Nice to Have' requirements (Python, Cloud, Remote). However, there is a significant stack gap: the role is strictly Full Stack JavaScript (Node/React), while the candidate is a Python/Systems specialist. Given the 'Junior' level and 'Fast Learner' trait (self-hosted LLMs, founder experience), the candidate has the aptitude to pivot quickly, but currently lacks the specific requested web frameworks.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate has strong automation, scripting (Python/Shell), and general infrastructure (Terraform/Docker) foundations suitable for SRE work. However, the role explicitly marks 'OpenStack' as indispensable, which is completely absent from the resume. He also lacks specific mentions of enterprise virtualization, messaging (RabbitMQ), and config management (Ansible), though his 'fast learner' profile suggests he could adapt quickly.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match driven by exceptional Domain + Tech synergy. Although the candidate lacks specific experience with the 'BigQuery/Airflow' stack, his background in Supply Chain (MicroMasters) and JIT Inventory systems makes him highly valuable for a Distribution-focused company. His proven ability to build complex 'metal-up' systems and perform Algorithmic Trading (Python/Pandas) confirms he possesses the required Data Engineering logic (ELT concepts). The missing tools (GCP, Airflow) are adjacent to his existing stack (AWS, Custom Python Automation) and can be learned rapidly given his 'Fast Learner' profile.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a high-potential architectural match with strong Python, automation, and infrastructure skills (Docker, Self-hosted AI). While lacking the specific 'Big Data' toolchain (Spark, Airflow, Snowflake), their proven ability to master complex domains (Algo Trading, LLMs) suggests rapid upskilling. Excellent cultural fit for innovation/challenges, but requires onboarding for the specific data stack.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is significantly overqualified (10+ years experience vs. 'Junior' role) with a strong domain match in Supply Chain and Logistics. While the resume focuses on code-first automation (Python, Pandas) rather than the requested GUI tools (MS Project, Power BI), his 'Fast Learner' profile and engineering background suggest he can master these specific tools immediately. The core competency of project management and financial analysis is fully present.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong domain alignment in Finance and Trading. However, there is a critical technical stack mismatch. The role requires a Microsoft ecosystem specialist (C#/.NET/WPF/SQL Server) and Full Stack UI work (Frontend/WPF), whereas the candidate is a Python/Infrastructure/Automation specialist focused on Backend and DevOps/AI. While a fast learner, the gap spans the entire core development stack.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate is a senior Python/Infrastructure engineer with strong AI/LLM background, but the job has a specific hard requirement for the 'Blip' platform (chatbots) and prefers .NET (C#), neither of which are listed in the resume. While the candidate's general engineering and AI skills are transferable, the specific tech stack mismatch is significant for this particular role.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is significantly overqualified, possessing advanced data engineering and automation skills (Python/Pandas) that far exceed the position's requirements for Excel-based analysis. While he lacks the specific 'Junior Project Analyst' title and Education/Public Policy domain experience, his background in Supply Chain planning and Financial Analysis demonstrates the required analytical and organizational capabilities.

[ANALYSIS_REPORT] [Model: gemini-cli] The candidate possesses the foundational academic background (Mechatronics Engineering) but has pivoted his career entirely toward IT, Cloud, and Financial Software. The role is a Senior Operational Technology (OT) position requiring deep, recent hands-on experience with specific industrial hardware (PLCs, Industrial Networks) which is absent from his professional history. While a fast learner, the gap between his current stack (Python/Docker/AI) and the required stack (Rockwell/Siemens/Profinet) is too wide for a Senior role without significant retraining.

[ANALYSIS_REPORT] [Model: gemini-cli] Significant domain mismatch. The role specifically requires a Network & Infrastructure Architect deeply embedded in the Cisco ecosystem (Hardware, Telephony, Enterprise Security), whereas the candidate is a Software, Automation & Data Architect. While the candidate has strong business acumen (ROI, TCO) and general 'Architect' traits, they lack the fundamental networking engineering background (CCNP level) and specific vendor knowledge required for this pre-sales role.

[ANALYSIS_REPORT] [Model: gemini-cli] Candidate is a strong Systems Architect with solid DevOps/Infrastructure skills (Docker, CI/CD, AWS basics) and a proven 'Fast Learner' ability. However, this is a Technical Lead role specifically for the Java/Spring ecosystem with React. The absence of the core programming language (Java) and framework (Spring Boot) makes it highly difficult to fulfill the 'mentoring' and 'standard definition' responsibilities immediately, despite general architectural alignment.

[ANALYSIS_REPORT] [Model: gemini-cli] Major Tech Stack Mismatch. The candidate is a Senior Python/Automation Architect, while the role requires a C#/.NET Developer. Although the candidate has strong engineering fundamentals (JIT systems, Algo trading) and is a proven fast learner who could adapt to C#, they currently lack the core Microsoft ecosystem tools (Visual Studio, .NET) and specific language requirements strictly demanded by the job description.

[ANALYSIS_REPORT] [Model: gemini-cli] Strong match for the 'Technical Background' requirement; the candidate's experience in Solution Architecture, DevOps (CI/CD, Docker), and 'Bridging Business & Tech' directly aligns with the role's need for a technical leader. His background in JIT/Supply Chain effectively covers the 'Value Stream Mapping' and process optimization requirements implicitly. The primary score deduction is due to the lack of explicit large-scale corporate Agile framework experience (SAFe, managing multiple distinct software squads) and formal certifications (CSM, PMP) requested.