Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] Strong signals on Linux and automation mindset, but the JD is specifically about building/operating OpenShift/Kubernetes clusters in production. The resume doesn’t demonstrate OpenShift/K8s cluster administration or 5+ years SRE experience. Improve only if there is real OpenShift/K8s ops work to add (cluster lifecycle, upgrades, troubleshooting, monitoring). **Strengths:** linux + scripting, automation/tooling orientation, production-minded engineering **Missing Required:** 5+ years as site reliability engineer, openshift/kubernetes deep experience

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT5.2] Boa aderência ao perfil multidisciplinar: integrações via API, documentação, resolução de incidentes e governança/visibilidade para stakeholders são temas fortes no histórico. Faltam evidências específicas de IT ops “hands-on” (gestão de equipamentos, cofre de senhas/iam interno) e do sistema EVO, mas não parecem bloqueadores absolutos. Para subir no ATS, adicionar bullets explícitos de administração/segurança (vault, permissões, SSO), exemplos de integrações e incidentes resolvidos com métricas. **Strengths:** API integration + troubleshooting mindset, Process/documentation + stakeholder management, Cloud familiarity + automation

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] The JD is a Google Staff Infra role requiring 8 years of C++ plus deep DS&A and large-scale distributed systems; the resume centers on Go/automation and ops tooling. This is a hard domain/tooling mismatch for ATS and human reviewers. Improve by targeting infra/platform roles matching Go/automation, not C++/Google Staff requirements. **Strengths:** systems thinking (general), automation orientation (general), engineering degree (general) **Critical Gaps:** required C++ + DS&A background not present; role is Staff-level Google infra **Missing Required:** 8 years programming in C++, 5 years shipping/testing software products, large-scale infrastructure/distributed systems experience at scale

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Candidate has strong systems architecture, automation, and infrastructure optimization skills that align with SRE philosophy. However, lacks direct Kubernetes experience (only Docker mentioned), no AWS production experience at scale, and no formal SRE/DevOps title history. Critical gap: no demonstrated Kubernetes expertise which is core to this Staff-level SRE role. To improve: add any Kubernetes learning/projects, emphasize Go production experience more prominently, and highlight incident response experience if any exists. **Strengths:** Go production experience (orchestrator), Systems architecture mindset, Linux proficiency **Critical Gaps:** Kubernetes production experience required **Missing Required:** Kubernetes and Container experience, High scalability challenges experience, AWS experience

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] There is partial overlap on Linux, DNS, access controls, and general infrastructure mindset, but the JD is corporate network/sysadmin (routing/switching/firewalls/VPN/VMware/Meraki) which isn’t clearly shown. ATS will treat the resume as software/automation-heavy rather than hands-on network administration. Improve by adding specific network/sysadmin accomplishments (VPNs, firewalls, Wi-Fi, virtualization, incident tickets) and tools/vendors used. **Strengths:** linux + scripting, dns/oauth/access-control awareness, clear problem-solving + operational ownership **Missing Required:** corporate network/system administration experience (explicit)

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Strong alignment with ERP systems (TOTVS hands-on), supply chain domain expertise (WMS/TMS concepts), API integrations, and business-technical translation. Candidate's deep TOTVS experience and supply chain background directly match retail systems requirements. Gap: no formal software development experience with SE title, and lacks specific retail PDV/payment systems knowledge. To improve: emphasize TOTVS integration work, add specific API integration examples, and mention any payment/POS adjacent experience. **Strengths:** Deep TOTVS/ERP experience, Supply chain domain (WMS/TMS concepts), API integration experience, Technical-business translation **Missing Required:** Software development experience in retail sector

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] This is a highly specialized Base24/NonStop (TAL/TACL/EMS) role with specific payments platform operations, which isn’t present in the resume. ATS will reject due to missing Base24 stack and domain knowledge. Improve by targeting LLM/automation/platform roles; this role requires an existing Base24 operator/engineer background. **Strengths:** sql (general), tcp/ip (general awareness), problem-solving mindset **Critical Gaps:** specialized Base24/NonStop payments platform domain mismatch **Missing Required:** base24 architecture/modules, nonstop tooling and commands, base24 networking configuration

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Embedded systems specialist role requiring deep C/C++, Java, Android/Google TV development, and TV Digital middleware expertise. Candidate has no embedded systems experience, no C/C++ or Java proficiency, no Android development background. Mechatronics degree provides some hardware concepts but no direct embedded software development. Complete domain mismatch despite engineering background. No realistic path to improve resume for this role. **Strengths:** Engineering degree, Linux familiarity **Critical Gaps:** Embedded systems development, C/C++ programming, TV Digital domain **Missing Required:** C/C++, Java, Embedded software development, TV Digital experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Mid-level SRE role with requirements for Linux, Docker, Kubernetes, AWS, monitoring, and CI/CD. Candidate has Linux, Docker, Git, CI/CD basics, and Python scripting. Missing Kubernetes hands-on, AWS experience, and observability stack. The orchestrator project in Go shows relevant systems thinking but lacks cloud-native tooling. To improve: highlight Docker usage, add any cloud exposure (even personal projects), emphasize automation and monitoring aspects of current work. **Strengths:** Linux proficiency, Docker basics, Automation mindset, Python/Go scripting **Missing Required:** Kubernetes experience, Cloud environment (AWS preferred)

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Game industry multiplayer systems engineering requiring C#, Unity, network programming, load testing infrastructure, and game engine experience. Candidate has no C# experience, no Unity/game engine background, no network code or multiplayer systems experience. Python and Go skills don't transfer directly. Gaming industry is highly specialized with specific tooling requirements. No realistic path to match this JD. **Strengths:** Python scripting, AWS basics mentioned, CI/CD understanding **Critical Gaps:** C# required, Unity/game engine required, Multiplayer networking domain **Missing Required:** C# proficiency, Unity or similar engine experience, Multiplayer systems experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Red Hat Ansible specialist role requiring 6+ years Ansible/AAP experience, playbooks, roles, inventories, workflows. Candidate has no Ansible experience mentioned in resume. Has automation background with n8n, custom orchestrators, and scripting but not Ansible-specific. Python knowledge is relevant but not sufficient. 6+ years requirement is a hard filter. To improve: if candidate has any Ansible exposure, add it prominently; otherwise this is not a viable role. **Strengths:** Python knowledge, Linux proficiency, Automation mindset, Git usage **Critical Gaps:** 6+ years Ansible experience required **Missing Required:** Ansible and AAP, 6+ years Ansible experience, Playbooks/roles/inventories hands-on

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] IT Security role emphasizing identity-centric security, automation, Zero Trust, and AI/LLM usage. Candidate has strong scripting (Python, Bash), OAuth/OIDC implementation experience, SSO knowledge, and demonstrated AI/LLM tool usage. Missing specific security domain experience (Conditional Access, MDM, compliance frameworks SOC2/HIPAA/GDPR). The AI/LLM angle is a genuine differentiator. To improve: emphasize OAuth 2.0/OIDC implementation, add any security-related automation, highlight AI tool usage for technical work. **Strengths:** Python/Bash scripting, OAuth 2.0/OIDC hands-on, AI/LLM tool proficiency, Automation focus **Missing Required:** Security domain experience, Compliance frameworks

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Implementation engineer for telecom requiring Linux admin, Kubernetes, networking, databases, troubleshooting. Candidate has strong Linux, PostgreSQL, networking basics (from systems work), troubleshooting mindset, and scripting. Kubernetes is listed as 'valorable' not required. Telecom/OSS/BSS domain is new but implementation focus matches candidate's hands-on style. To improve: emphasize Linux server administration, database setup experience, add networking details from infrastructure work. **Strengths:** Linux administration, PostgreSQL hands-on, Troubleshooting/debugging, Bash scripting, Production deployment experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Senior Cloud Platform Engineer requiring Linux, Ansible, Terraform, VMware/KVM, networking, observability. Candidate has Linux, Python, Go, Bash scripting, PostgreSQL but lacks Ansible, Terraform, and virtualization experience. Cloud experience is foundational only. 2+ years System Admin or 1+ year DevOps/SRE required - candidate has neither title. To improve: highlight any infrastructure automation, add cloud project details, emphasize production systems management. **Strengths:** Linux proficiency, Python/Go/Bash scripting, PostgreSQL, Production systems experience **Missing Required:** Ansible, Terraform or similar, 2+ years SysAdmin or 1+ year DevOps/SRE title

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] RSA Archer platform specialist requiring advanced Archer knowledge, AWS, and infrastructure background. RSA Archer is a specialized GRC (Governance, Risk, Compliance) platform - candidate has no exposure to this or similar tools. AWS is required but candidate only has fundamentals. ITIL, ServiceNow, Azure DevOps mentioned as differentials - none present. Complete platform specialization mismatch. **Strengths:** Some AWS fundamentals, SQL knowledge **Critical Gaps:** RSA Archer expertise required **Missing Required:** RSA Archer advanced knowledge, AWS experience, Infrastructure background

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] AI Architect role requiring 7+ years architecture experience, LLM/GenAI expertise, LangChain, multi-agent systems, cloud AI infrastructure. Candidate has LangChain, RAG, LLM pipeline design, embedding models, Claude/Gemini/OpenAI API experience. However, lacks 7+ years in formal architecture roles, no MLOps/DevOps background, and multi-agent experience is not explicitly demonstrated. Strong alignment on GenAI tooling but gaps in formal architecture credentials. To improve: quantify architecture decisions, emphasize LangChain/RAG work, add any multi-agent exploration. **Strengths:** LangChain experience, RAG implementation, LLM API expertise (Claude, Gemini, OpenAI), Embedding models, Production AI pipeline **Missing Required:** 7+ years architecture/engineering experience in formal role

[ANALYSIS_REPORT] **HIGH** [Opencode: opus-4-5] AI Solutions Engineer (Remote) requiring 3+ years AI/ML, Python, ML frameworks, cloud deployment, business-to-technical translation. Candidate has Python, AI/ML pipeline experience, LLM APIs, business translation skills, and production deployment. 3+ years AI/ML is borderline but recent intensive work counts. Remote work and BairesDev connection (potential outsourcing) noted. To improve: emphasize ML pipeline work, quantify AI project outcomes, highlight business translation explicitly. **Strengths:** Python for AI, LLM API expertise, Business-to-technical translation, Production AI deployment, Cloud basics

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Data Scientist III requiring Masters (PhD preferred), cloud infrastructure leadership, full-stack development, MLOps/DeepOps, and extensive ML/DL expertise (CNNs, RNNs, Transformers). Candidate has Bachelor's only (no Masters), lacks deep ML/DL framework expertise, no PyTorch/TensorFlow hands-on, no industrial AI implementation. Leadership and cloud aspects partially align but core data science credentials are missing. **Strengths:** Python, AI pipeline basics, Cloud awareness **Critical Gaps:** Masters degree required, Deep Learning expertise **Missing Required:** Masters degree, Deep ML/DL knowledge, PyTorch/TensorFlow, Industrial AI implementation

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Senior MLE/Data Engineer for MLOps, model deployment, and GenAI. Candidate has LLM pipeline experience, cloud awareness (AWS basics), and GenAI tooling. Missing formal MLOps experience, model lifecycle management, and software engineering background for ML systems. GenAI knowledge is a differentiator mentioned. To improve: emphasize LLM pipeline as MLOps-adjacent, add model deployment details, highlight GenAI practical experience prominently. **Strengths:** GenAI practical experience, LLM pipeline design, AWS fundamentals, Python **Missing Required:** MLOps experience, Software engineering base for ML

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Mid-level MLE/Data Engineer for MLOps, model deployment, GenAI support. Similar to senior role but with lower experience bar. Candidate's GenAI experience, LLM pipelines, and Python skills are relevant. MLOps gap remains but mid-level is more accessible. Open-source familiarity (published CMS) aligns with requirement. To improve: same as senior role - emphasize LLM pipeline as MLOps-adjacent, highlight open-source work. **Strengths:** GenAI practical experience, Open-source contribution, LLM pipeline design, AWS fundamentals, Python **Missing Required:** MLOps experience

[ANALYSIS_REPORT] **MEDIUM** [3-Flash] The candidate demonstrates strong technical proficiency in AI pipelines and automation, specifically through the creation of a custom Go orchestrator and AI scoring system. The absence of an official 'Software Engineer' title is mitigated by the recent high-complexity project involving Docker and production-grade scrapers. To improve, the candidate should explicitly mention MLOps governance frameworks like MLflow in the resume. **Strengths:** AI pipeline architecture, Docker/Containerization, Automation & CI/CD **Missing Required:** Direct experience with GCP (only generic cloud mentioned)

[ANALYSIS_REPORT] **LOW** [3-Flash] While the candidate has the foundational skills (Linux, AWS, Python), the JD explicitly requires 'strong experience with Terraform' and Kubernetes (EKS), which are not prominently featured as core professional competencies. The technical level is appropriate, but the tool-specific requirements create a gap. Adding Terraform projects to the portfolio is essential. **Strengths:** AWS fundamentals, Linux/Redes, Python/Shell automation **Critical Gaps:** Terraform expertise **Missing Required:** Proven IaC experience, K8s orchestration

[ANALYSIS_REPORT] **TOP** [3-Flash] Excellent alignment with the 'AI Software Architect' profile, as the candidate recently built a scalable AI platform using LLM APIs and custom Go microservices. The Mechatronics degree is a strong substitute for CS in high-performance architecture. To optimize, the candidate should map his 'Go orchestrator' functions to AWS-specific terms like Lambda or ECS. **Strengths:** LLM production experience, API/System Design, Technical-Business bridge **Missing Required:** Official 'Software Architect' title

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT5.2] Strong match: proven AI product delivery to production, LangChain/RAG/embeddings, OpenAI-style SDK usage, and building full systems (scraper + scoring + site) with measurable evaluation outcomes. Minor gaps are specific tools like Promptfoo/LangSmith/Azure AI, but the core capabilities are clearly demonstrated. Improve by adding an explicit “AI product shipped” section (API endpoints, eval suite design, monitoring, user impact) and naming any vector DB/pgvector usage if applicable. **Strengths:** rag + embeddings + llm pipeline design, production system shipped end-to-end, go/js/python + sql/postgres for APIs/workflows

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] The resume shows LLM integration, RAG, data pipelines, and Python capability, but the JD is framed as AI/ML engineering with model training pipelines and ML frameworks, which aren’t evidenced. ATS will treat this as “LLM app/infra” rather than “ML engineer.” Improve by adding concrete ML work (PyTorch/Sklearn, training/evaluation, feature pipelines) or repositioning toward LLM/AI platform roles. **Strengths:** python + data/automation mindset, rag/llm systems in production, systems/infrastructure orientation for deployment **Missing Required:** 3+ years AI/ML engineering experience (explicit), model training pipeline experience