Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **HIGH** [2.5-Pro] The candidate's profile is a strong match for designing scalable and secure AI solutions and translating business needs into technical architecture, as demonstrated by his recent platform project. His hands-on experience with security and production systems is a major plus. The score is capped because explicit keywords like 'LGPD' and 'data governance', while inferable from his work, are not present and could be filtered by an ATS. **Strengths:** Scalable AI architecture design, Hands-on implementation skills, Translating business requirements

[ANALYSIS_REPORT] **LOW** [2.5-Pro] This role is fundamentally centered around the SAP ecosystem, a technology stack with which the candidate has no experience. While he has transferable skills in AI, integration, and leadership, the lack of SAP knowledge is a critical gap. His ERP experience with TOTVS is not equivalent in this context, leading to a score capped at 40. **Strengths:** AI Implementation, API Standardization Concepts, Technical Leadership **Critical Gaps:** No experience with SAP **Missing Required:** SAP

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] AI Technical/Solution Architect requiring 10-20+ years experience, Azure AI services expertise, AZ-204 certification, and PySpark. Candidate has no Azure experience, no certifications, and vastly insufficient years. The Master's degree preference and Microsoft certification requirement are hard barriers. **Strengths:** Prompt engineering, AI integration concepts, Generative AI understanding **Critical Gaps:** 10+ years Technical Architect experience, AZ-204 certification required, Azure platform expertise **Missing Required:** Microsoft Azure certification, Hybrid/cloud architecture experience

[ANALYSIS_REPORT] **LOW** [Copilot: GPT4.1] The person lacks the required 5+ years of hands-on Azure experience, direct experience with Azure OpenAI, Form Recognizer, Cognitive Search, and the Microsoft AZ-204 certification. While there is strong AI, automation, and systems architecture experience, the absence of deep Azure and specific Microsoft stack expertise is a critical gap. To improve, the person should gain hands-on Azure project experience and obtain the required certification. **Strengths:** AI architecture, Prompt engineering, Team leadership **Critical Gaps:** 5+ years hands-on Azure experience, Microsoft Certified: Azure Developer Associate (AZ-204) **Missing Required:** Azure OpenAI, Form Recognizer, Cognitive Search, AZ-204 certification

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person demonstrates strong AI, automation, data integration, and client-facing experience, with deep skills in Python, SQL, and workflow automation. The main missing skills are direct experience with marketing platforms and some MarTech-specific tools, but these are not critical. To improve, the person could highlight any relevant marketing analytics or MarTech project experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Data integration and architecture

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person matches nearly all requirements, including AI/LLM, workflow automation, Python, SQL, and client-facing leadership. The only notable gap is direct experience with specific MarTech platforms and tools, but this is not a critical blocker. To improve, the person should highlight any relevant MarTech or marketing analytics experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Python and data integration

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person meets most requirements for solution architecture, AI, cloud, and team leadership, but lacks direct experience with large enterprise platforms and may not have formal certifications. The resume shows strong systems and automation skills, but lacks evidence of experience in multiple business domains or public thought leadership. To improve, the person should highlight any enterprise-scale projects and consider obtaining relevant certifications. **Strengths:** AI and automation, Systems architecture, Team leadership

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The candidate has the technical skills to build the PoCs and design the architectures required, but the role is in pre-sales, a function he has no demonstrated experience in. The job requires client-facing skills, proposal writing, and effort estimation in a sales context, which are significant gaps. He is a builder, not a seller, resulting in a low score. **Strengths:** Technical PoC development, Data engineering concepts, Cloud fundamentals **Critical Gaps:** Lack of client-facing pre-sales experience **Missing Required:** Experiência prévia com pré-vendas técnicas

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person matches most requirements, including backend, AI, DevOps, and leadership, but lacks direct .NET experience and legacy refactoring background. Azure experience is present but not deep. To improve, the person should highlight any Azure projects and address .NET or legacy system exposure if possible. **Strengths:** AI technologies, Backend and DevOps, Technical leadership

[ANALYSIS_REPORT] **MEDIUM** [2.5-Pro] The role's requirement for a technical leader proficient in 'Python or Go' and 'arquitetura em microserviços' is a perfect match for the candidate's core skills. However, the JD also specifically lists deep learning frameworks (TensorFlow, PyTorch) and MLOps, which are areas where the candidate's experience is more in using LLM APIs rather than training models from scratch. This gap in core ML tooling prevents a higher score and caps it at 70. **Strengths:** Go and Python proficiency, Microservices Architecture, Technical Leadership **Missing Required:** Desenvolvimento de algoritmos de Machine Learning/Deep Learning

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person matches nearly all requirements, including AI/LLM, workflow automation, Python, SQL, and client-facing leadership. The only notable gap is direct experience with specific MarTech platforms and tools, but this is not a critical blocker. To improve, the person should highlight any relevant MarTech or marketing analytics experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Python and data integration

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person matches nearly all requirements, including AI/LLM, workflow automation, Python, SQL, and client-facing leadership. The only notable gap is direct experience with specific MarTech platforms and tools, but this is not a critical blocker. To improve, the person should highlight any relevant MarTech or marketing analytics experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Python and data integration

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person meets most requirements for solution architecture, AI, cloud, and team leadership, but lacks direct experience with large enterprise platforms and may not have formal certifications. The resume shows strong systems and automation skills, but lacks evidence of experience in multiple business domains or public thought leadership. To improve, the person should highlight any enterprise-scale projects and consider obtaining relevant certifications. **Strengths:** AI and automation, Systems architecture, Team leadership

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person matches nearly all requirements, including AI/LLM, workflow automation, Python, SQL, and client-facing leadership. The only notable gap is direct experience with specific MarTech platforms and tools, but this is not a critical blocker. To improve, the person should highlight any relevant MarTech or marketing analytics experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Python and data integration

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person matches nearly all requirements, including AI/LLM, workflow automation, Python, SQL, and client-facing leadership. The only notable gap is direct experience with specific MarTech platforms and tools, but this is not a critical blocker. To improve, the person should highlight any relevant MarTech or marketing analytics experience. **Strengths:** AI/LLM workflow automation, Client-facing technical leadership, Python and data integration

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person meets most requirements for solution architecture, AI, cloud, and team leadership, but lacks direct experience with large enterprise platforms and may not have formal certifications. The resume shows strong systems and automation skills, but lacks evidence of experience in multiple business domains or public thought leadership. To improve, the person should highlight any enterprise-scale projects and consider obtaining relevant certifications. **Strengths:** AI and automation, Systems architecture, Team leadership

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person demonstrates strong experience in AI architecture, multiagent systems, RAG, and technical leadership, with deep Python and automation skills. The only notable gap is direct experience with LangChain/LangGraph/Semantic Kernel, but adjacent skills are present. To improve, the person should highlight any multiagent or RAG project experience and mention familiarity with these frameworks. **Strengths:** AI architecture, Multiagent systems, Technical leadership

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person meets most requirements for solution architecture, AI, cloud, and team leadership, but lacks direct experience with large enterprise platforms and may not have formal certifications. The resume shows strong systems and automation skills, but lacks evidence of experience in multiple business domains or public thought leadership. To improve, the person should highlight any enterprise-scale projects and consider obtaining relevant certifications. **Strengths:** AI and automation, Systems architecture, Team leadership

[ANALYSIS_REPORT] **LOW** [2.5-Pro] While the role's focus on AI agents, RAG, and building platforms is a near-perfect match for the candidate's skills, the hard requirement of '10+ anos em engenharia de software/arquitetura' acts as an automatic filter. The candidate has over a decade of experience, but not with those specific titles, which an ATS will interpret as 0 years of experience, resulting in an automatic rejection. **Strengths:** AI Agent Architecture, Advanced RAG, Platform Building **Missing Required:** 10+ years in software engineering/architecture title

[ANALYSIS_REPORT] **TOP** [Copilot: GPT4.1] The person demonstrates strong AI, automation, and agentic systems experience, with deep skills in Python, workflow automation, and data pipelines. The only notable gap is direct experience with specific mobility/payment platforms, but this is not a critical blocker. To improve, the person should highlight any relevant experience in mobility, payments, or compliance. **Strengths:** AI/LLM workflow automation, Agentic systems, Data pipelines

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This is an extremely strong match. The role requires a Python developer to build agents with LangChain, implement RAG, and work with microservices—all technologies the candidate has direct, recent experience with. His project work demonstrates practical application of the exact concepts and tools mentioned in the job description, justifying a very high score. **Strengths:** Python, LangChain and Agentic Workflows, RAG with Vector Databases

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The job description is extremely vague, indicating a consulting or staff augmentation role. Based on the 'MLOps Engineer' title, the candidate matches on foundational skills like CI/CD, Docker, and cloud platforms. However, he lacks explicit experience with core MLOps tools (like Kubeflow, MLflow) and Kubernetes, which are typically required for such roles. **Strengths:** CI/CD, Docker, Python, Cloud Fundamentals

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person has strong experience in AI infrastructure, automation, and CI/CD, but lacks direct MLOps pipeline and Kubernetes experience. The resume shows deep systems and automation skills, but does not explicitly mention MLOps or model monitoring at scale. To improve, the person should highlight any MLOps, model monitoring, or Kubernetes experience. **Strengths:** AI infrastructure, Automation, CI/CD

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT5.1] The candidate is a very strong semantic match for an API Integration Engineer focused on AI/LLM, with concrete proof of integrating Claude/Gemini/OpenAI APIs, building scrapers, orchestrators, and a production web server. They demonstrate deep experience designing and consuming REST APIs, orchestrating cross-system workflows, and making LLM-powered systems reliable on constrained infrastructure, which hits the core of the JD. To improve, the resume should explicitly reference "API integration", "enterprise integration" and "Model Context Protocol-style" patterns, and surface more Python-focused integration examples (even if most current code is in Go). **Strengths:** Production LLM API integrations and pipelines, Custom Go-based orchestrator for multi-service workflows, Strong REST API design, scraping, and automation background

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This is an almost perfect fit. The job requires building a corporate AI platform, including a CLI, an agent runtime, and an LLM Gateway, using Node.js or Python and OAuth. This aligns directly with the candidate's recent project where he built an orchestrator, used OAuth, and has deep experience in both languages. His platform-building mindset is exactly what's needed. **Strengths:** AI Platform Architecture, Agent Runtime Concepts, Node.js/Python and OAuth experience