Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] Existe match em backend/arquitetura (Go, OAuth/OIDC, Linux, webserver), mas a vaga exige full stack com frameworks modernos (React/Angular/Vue) e domínio de CSS/Frontend, que não está demonstrado. O ATS tende a tratar ausência de framework frontend como lacuna de requisito. Para melhorar: evidenciar um app com React/TypeScript (mesmo pequeno) + testes e CI/CD, e listar microserviços/arquitetura distribuída com exemplos concretos. **Strengths:** Golang e sistemas em produção, segurança de auth (OAuth/OIDC), CI/CD e Linux/Docker (base) **Missing Required:** experiência full stack com framework frontend moderno, histórico explícito de atuação como Software Engineer full stack

[ANALYSIS_REPORT] **TOP** [Copilot: GPT5.2] O candidato tem provas recentes e diretas em Go (webserver/orquestrador), bancos relacionais (PostgreSQL/SQLite), Linux, Docker, OAuth/OIDC e troubleshooting em produção — alinhamento forte com um especialista Golang. O principal risco é falta de evidência explícita de cloud pública/Kubernetes/microserviços em escala, que muitos ATS esperam para “Cloud products”. Para subir ainda mais: incluir detalhes de testes, observabilidade (metrics/tracing), e qualquer experiência hands-on com AWS/GCP + deploy. **Strengths:** Golang em produção (sistemas reais), SQL/PostgreSQL + arquitetura, Linux/Docker + segurança (OAuth/OIDC)

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] Role requires a Microsoft-stack enterprise Data Engineer (Azure Data Factory, Snowflake, SSIS, SSAS). The candidate's background is mostly AWS/Linux, PostgreSQL, and custom pipeline scripting, completely missing the enterprise ETL toolings requested. **Strengths:** SQL, Python, Data transformation **Critical Gaps:** Enterprise ETL tooling (ADF, Snowflake) **Missing Required:** Experience with Azure Data Factory

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] A vaga é senior mobile (React Native/Flutter), publicação em stores, CI/CD mobile (Fastlane) e domínio de arquitetura de apps, e o currículo não mostra experiência mobile. Isso é um gap de domínio, não apenas ferramenta adjacente. Para competir: precisar de histórico real de apps RN/Flutter com release, métricas e testes E2E. **Strengths:** OAuth/OIDC e segurança de auth (conceitos), engenharia de backend/sistemas, integração via APIs **Critical Gaps:** domínio mobile (iOS/Android) obrigatório não atendido **Missing Required:** 3+ anos em desenvolvimento mobile (React Native/Flutter), arquitetura mobile e práticas (E2E, release)

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] Como banco de talentos, o requisito tende a ser mais flexível, e há aderência parcial em backend/automação (Go/Node/SQL) e visão de produto. Ainda assim, o ATS para “Full Stack” costuma priorizar React/TypeScript e experiência em times de software, que não estão claros. Para melhorar: adicionar um projeto demonstrável em React/TS + API + testes e alinhar o título/summary para “Software Engineer / Full Stack” com bullets técnicos. **Strengths:** backend e sistemas em produção (Go/Node), SQL e arquitetura de dados leve, automação e entrega rápida **Missing Required:** experiência full stack com framework frontend moderno (provável filtro)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] A vaga é SR backend .NET/C# + AWS e modernização em escala; o candidato tem backend/arquitetura (Go, Linux, Docker), mas não evidencia .NET/C# nem AWS hands-on relevante. Para esse tipo de cargo, stack específica pesa mais que equivalência por categoria. Para melhorar: só faria sentido se houvesse experiência real em C#/.NET (serviços, testes) e AWS (serverless/K8s) com exemplos. **Strengths:** arquitetura e produção em Go, Linux/Docker + troubleshooting, integração e segurança (OAuth/OIDC) **Missing Required:** experiência sólida em backend .NET/C#, AWS (serverless) com evidência prática

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] Há aderência em Python/SQL, arquitetura e preocupação com robustez/monitoramento, mas faltam as âncoras do cargo: PySpark/Spark, stack AWS de dados (S3/Glue/Athena/Redshift etc.) e dbt/modelagem dimensional. O ATS para data engineering em escala é muito orientado a ferramentas e volume. Para melhorar: incluir experiência com Spark (mesmo em cluster gerenciado), dbt (modelos/medalhão) e exemplos de pipelines em cloud com SLA/observabilidade. **Strengths:** Python + SQL (base sólida), arquitetura e automação de sistemas, mentalidade de qualidade/validação e produção **Missing Required:** processamento distribuído com Spark/PySpark, vivência com serviços cloud de dados, arquitetura medalhão/dbt/modelagem dimensional em escala

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical gaps: Missing all required AWS certifications (SA Pro, Data Engineer Associate, AI Practitioner) which are mandatory hard requirements. Mechatronics Engineering may not pass ATS 'IT area' degree filter. Despite 12+ years of systems architecture work, ATS will not recognize 'Financial Analyst' or 'Supply Chain Planner' titles as Solutions Architect experience. **Strengths:** Data pipeline architecture, Cloud fundamentals, Technical translation **Critical Gaps:** Required AWS certifications, Formal Solutions Architect title, IT-specific degree **Missing Required:** 6 years Solutions Architect experience, AWS certifications, Bachelor's in IT

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Strong match on architecture fundamentals, CI/CD, and cloud environments. Candidate's Go orchestrator and automation systems demonstrate scalable architecture design. Missing enterprise environment experience slightly caps score. **Strengths:** Systems architecture, DevOps/CI/CD, APIs and distributed systems, Cloud environments

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical gaps dominate: Zero SAP experience (BW on HANA, DataSphere, SAC, BTP) despite deep expertise requirements. No industrial or mining sector background. TOGAF/Zachman framework knowledge absent. Resume demonstrates strong data architecture but in entirely different stack. **Strengths:** Data governance concepts, Data architecture principles, Integration patterns **Critical Gaps:** SAP ecosystem experience, Industrial/Mining sector, Enterprise Architecture frameworks **Missing Required:** 2 years Solutions Architect role, 2 years Industrial/Mining, SAP Data Landscape expertise

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical SAP knowledge gaps: No S/4HANA, FI/SD/MM modules, BTP, or Integration Suite experience required for Finance & Insurance domain. Clean Core strategy and FSCD knowledge absent. Candidate's ERP experience is limited to TOTVS, not SAP. **Strengths:** ERP data remediation, Financial business logic, Systems integration **Critical Gaps:** SAP ecosystem expertise, Financial services domain **Missing Required:** SAP S/4HANA experience, FI module expertise

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical gaps: No Salesforce, Veeva, or LifeScience Cloud experience. Agentforce/AI agent orchestration not demonstrated with Salesforce stack. Candidate's AI experience is with raw LLM APIs, not Salesforce ecosystem. **Strengths:** AI agent design, LLM integration, API orchestration **Critical Gaps:** Salesforce platform expertise, LifeScience domain **Missing Required:** 5 years Salesforce/Veeva

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Excellent technical match: Cloud (AWS/Azure/GCP), APIs, messaging, distributed architecture, DevOps/CI/CD all demonstrated through production Go orchestrator and automation systems. English fluent. Hybrid format compatible with São Paulo location. **Strengths:** Cloud environments, CI/CD pipelines, Distributed architecture, APIs and messaging, Systems modernization

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Job is entirely SAP S/4HANA focused despite only formally requiring Bachelor's degree. Candidate has zero SAP experience. Pre-sales and architecture skills present but wrong technology stack entirely. **Strengths:** Architecture design, Pre-sales support, Systems implementation **Critical Gaps:** SAP ecosystem

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical gap: Requires 8+ years NetSuite ERP experience. Candidate has zero NetSuite exposure. SuiteScript, SuiteFlow, SuiteAnalytics, SuiteBilling all absent. O2C/P2P process knowledge exists but not in NetSuite context. **Strengths:** ERP systems, O2C/P2P processes, Integration architecture **Critical Gaps:** NetSuite platform expertise, 8 years NetSuite architecture **Missing Required:** 8 years NetSuite experience

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Role is SAP S/4HANA Cloud/RISE pre-sales. Candidate meets formal requirements (Bachelor's, English) but lacks SAP technology knowledge required for credible customer presentations. Spanish requirement also not met. **Strengths:** Pre-sales support, Technical presentations, Architecture explanation **Critical Gaps:** SAP ecosystem expertise **Missing Required:** SAP technology knowledge

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Strong technical foundation: TCP/IP, HTTP, DNS, Linux, scripting (Go/Python), security (OAuth/WAF concepts), web performance optimization all demonstrated. Missing CDN-specific and deep networking (BGP, TLS) experience caps score at 85. **Strengths:** Network protocols, Web performance optimization, Security solutions, Scripting, Linux, Reverse proxy concepts

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Good match for cloud architecture and pre-sales support. Financial sector exposure from previous roles. Multi-cloud knowledge limited to fundamentals but architecture principles transfer. Curiosity/self-taught nature matches candidate profile. **Strengths:** Cloud architecture, Pre-sales technical support, Solution demonstrations, Financial sector experience, Automation

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Identical requirements to Job 6 with strong technical match. Cloud, APIs, distributed architecture, DevOps/CI/CD all demonstrated. English fluent. Hybrid work in Barueri compatible with location. **Strengths:** Cloud environments, CI/CD, Distributed architecture, APIs, System modernization

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical domain mismatch: Role requires 5-8 years in network architecture (LAN, WLAN, WAN, SD-WAN) with Cisco/Aruba/HPE certifications. Candidate has general Linux/networking but no enterprise networking specialization. **Strengths:** Linux networking, OAuth/security, Infrastructure, System architecture **Critical Gaps:** Network architecture specialization, Required certifications **Missing Required:** 5-8 years connectivity solutions, Bachelor's in Networks/Telecom

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical gaps: Zero RPA tool experience (UiPath, Blue Prism, Automation Anywhere). No .NET/Java background mentioned. Requires Automation Anywhere Advanced certification. Candidate's automation is code-based (Go/Python), not RPA. **Strengths:** Process automation, Workflow design, Python scripting **Critical Gaps:** RPA platform expertise, Required certification **Missing Required:** Automation Anywhere Advanced certification, 3 years technology roles

[ANALYSIS_REPORT] **TOP** [Opencode: opencode:kimi-k2.5] Exceptional match: Strong Python, production AI agents (job intelligence platform with PID-control tuning), scikit-learn integration, LLM APIs (Claude, OpenAI), and explicit validation of AI-generated code mentioned in profile. Candidate's recent work is exactly this role. **Strengths:** Python production systems, AI agents, LLM integration, scikit-learn, AI code validation, RAG, Autonomous decision systems

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The score is zero due to the hard requirement for on-site work in Holambra, SP, which conflicts with the candidate's location in São Paulo. While the candidate's skills in AI application and automation are relevant, this geographical mismatch acts as an automatic filter. The resume could be improved by explicitly stating openness to relocation if that were an option. **Strengths:** IA implementation, Automation, Data Analysis **Critical Gaps:** On-site location requirement **Missing Required:** On-site work in Holambra, SP

[ANALYSIS_REPORT] **TOP** [2.5-Pro] The candidate shows strong alignment with core requirements like GenAI, Python, RAG, and vector DBs, demonstrated through the market intelligence platform project. The score is capped at 85 because, while proficient in AWS fundamentals, the JD explicitly requires Azure experience, which is a missing skill. To improve, the person should highlight any Azure exposure or frame their cloud skills as platform-agnostic, focusing on concepts like containers and functions which are transferable. **Strengths:** GenAI project leadership, Python, RAG architecture, CI/CD experience **Missing Required:** Azure

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This role is an almost perfect match, aligning directly with the candidate's demonstrated experience in automation (n8n, Make), integrations (APIs, Webhooks), databases (PostgreSQL), and languages (Python, JS). The recent project building a full platform with an AI assistant mirrors the JD's core responsibilities. The score isn't 100 only because the JD asks for 2 years of experience in a similar role, which the person has in practice but not by official job title. **Strengths:** Automation tools (n8n, Make), API integration (REST, OAuth 2.0), Python/JS, Building AI assistants