Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] The role strictly focuses on Computer Vision and point cloud manipulation. The candidate's data and AI experience is strictly related to text, LLMs, structured databases, and business operations. The ATS will assign a severe penalty for missing these critical domain keywords. **Strengths:** Python, Predictive modeling intuition **Critical Gaps:** Computer Vision, Point Clouds **Missing Required:** Computer Vision experience

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] This position requires advanced knowledge of image-based generative models (GANs, Diffusion) and deep framework optimization (TensorFlow, ONNX). The candidate specializes in text-based LLMs, API orchestration, and RAG. This is a fundamental mismatch in the type of Generative AI being utilized. **Strengths:** Python **Critical Gaps:** Image Generation, Deep Learning Frameworks **Missing Required:** TensorFlow/Keras advanced domain

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] Another pure Computer Vision role requiring OpenCV, Yolo, and image/video processing. The candidate has no practical experience with these technologies. The skill set is entirely disjointed from the requirements. **Strengths:** Python, Git **Critical Gaps:** Computer Vision **Missing Required:** Computer vision experience, OpenCV

[ANALYSIS_REPORT] **HIGH** [gemini-3.1-pro-preview] Excellent technical match for LLM Agents, prompt engineering, RAG, and guardrails. The candidate's recent projects exactly mirror these requirements. The ATS score is capped at 70 only because of the strict academic requirements (Masters/PhD) and the specific 'Pesquisadora' title preference, which the candidate lacks. **Strengths:** LLM Agents, Prompt Engineering, RAG, Guardrails **Missing Required:** Masters/PhD or 5 yrs R&D formal title

[ANALYSIS_REPORT] **TOP** [gemini-3.1-pro-preview] This is a perfect fit. The role requires a bridge between product management, business discovery, and hands-on AI execution using tools like Claude/Cursor to build functional code. The candidate literally acts as this bridge ('Ponte Técnico-Negócio') and has built a full market intelligence platform using GenAI. ATS will score this very high. **Strengths:** Technical-Business Translation, GenAI for prototyping, End-to-end delivery

[ANALYSIS_REPORT] **HIGH** [gemini-3.1-pro-preview] Strong alignment with the candidate's GenAI background, specifically regarding LLMs, agents, LangChain, APIs, and prompt injection mitigation. Similar to Job 9, the ATS score is suppressed by the strict academic requirements (Masters/PhD) typical of 'Researcher' roles, despite having the exact technical skills required. **Strengths:** LLM API Integration, Prompt Engineering, Agent Orchestration **Missing Required:** Masters/PhD

[ANALYSIS_REPORT] **MEDIUM** [gemini-3.1-pro-preview] The candidate has the necessary practical skills (LangChain, Python, Vector DBs, RAG, prompt engineering). However, the job demands a highly academic background (Graduation AND Doctorate) and formal ML Engineering titles, which will severely impact the ATS score. The environment seems highly specialized (Architecture/Urbanism). **Strengths:** LangChain, Vector DBs, RAG **Missing Required:** Doctorate degree

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] While the candidate has excellent LLM, Python, and leadership skills, this role specifically requires advanced expertise in traditional ML frameworks (TensorFlow, PyTorch, scikit-learn). The candidate is an AI orchestrator and systems builder, not a deep learning model trainer. ATS will dock points for missing core ML frameworks. **Strengths:** LLMs, Python, CI/CD, Leadership **Missing Required:** TensorFlow or PyTorch expertise

[ANALYSIS_REPORT] **MEDIUM** [gemini-3.1-pro-preview] The candidate possesses strong skills in GenAI, RAG, REST APIs, and Python. However, the role heavily leans into legacy conversational platforms (Watson, Lex, Dialogflow) and intent modeling, which the candidate hasn't used, favoring modern autonomous LLM agents instead. ATS will score moderately high based on NLP and Python. **Strengths:** GenAI, RAG, Python, REST APIs

[ANALYSIS_REPORT] **TOP** [2.5-Pro] The score is exceptionally high because the candidate's recent 'Job Intelligence Platform' project is a perfect, real-world demonstration of every skill required for this role. He has hands-on experience building AI workflows, using modern AI tools (Claude/Gemini), integrating APIs, and web scraping. The resume proves he can build practical solutions quickly, making him an ideal, albeit overqualified, fit. **Strengths:** AI agent and workflow automation, API integration, Python/JavaScript proficiency, Web scraping and data pipelines

[ANALYSIS_REPORT] **LOW** [gemini-3.1-pro-preview] Technically, this is an excellent match (n8n, APIs, GenAI for leads, CRM automation). However, the job strictly requires on-site presence (Presencial) in Brasília. The candidate is based in São Paulo. This is a hard demographic filter. **Strengths:** n8n, Make, GenAI, REST APIs **Critical Gaps:** Geographic location **Missing Required:** Presencial in Brasília

[ANALYSIS_REPORT] **TOP** [2.5-Pro] The candidate's profile is a strong match for the core responsibilities, particularly in building production AI systems and data pipelines, as evidenced by his market intelligence platform. He possesses the required LLM, RAG, and Python skills. To improve, the candidate should create a small project using FastAPI to directly address the missing framework experience, and rephrase parts of his resume to highlight API development outcomes more explicitly. **Strengths:** Production AI/LLM Pipelines, End-to-end System Architecture, API Integration **Missing Required:** FastAPI

[ANALYSIS_REPORT] **TOP** [2.5-Pro] The score is exceptionally high because the candidate's recent 'Job Intelligence Platform' project is a perfect, real-world demonstration of every skill required for this role. He has hands-on experience building AI workflows, using modern AI tools (Claude/Gemini), integrating APIs, and web scraping. The resume proves he can build practical solutions quickly, making him an ideal, albeit overqualified, fit. **Strengths:** AI agent and workflow automation, API integration, Python/JavaScript proficiency, Web scraping and data pipelines

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This role is an almost perfect match, aligning directly with the candidate's trajectory of applying AI and automation to solve concrete business problems in finance and operations. His deep experience with ERPs is a significant differentiator that directly maps to the job's needs. The resume needs no modification for this application, as his projects and skills are exceptionally well-aligned. **Strengths:** Business Process Automation, Applied AI for Operations, ERP Integration Experience (TOTVS)

[ANALYSIS_REPORT] **HIGH** [2.5-Pro] The candidate is a strong technical fit, with proven experience building API-heavy backend systems and using AI frameworks like RAG. However, the score is capped at 70 because the resume lacks the '5+ years software development experience' with a traditional SWE title, which is a major ATS filter. To improve, the candidate should reframe job descriptions to emphasize software engineering functions over operational titles. **Strengths:** Building API-heavy backend systems, Infrastructure ownership (CI/CD, deployment), Hands-on experience with LLMs and RAG **Missing Required:** 5+ years software development experience (by title)

[ANALYSIS_REPORT] **MEDIUM** [2.5-Pro] The candidate has strong foundational skills in backend development (Node.js, PostgreSQL), automation (n8n, LangChain), and core AI concepts (RAG, agents) required for the role. However, his lack of direct, hands-on experience in building production chatbots is a required skill gap that caps the score. To improve, he would need to build a portfolio project demonstrating chatbot development. **Strengths:** Backend Development (Node.js, PostgreSQL), AI Agent & RAG Architecture, Automation Tools (n8n, LangChain) **Missing Required:** Experiência real construindo chatbots em produção

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The candidate possesses foundational skills in architecture, Python, and prompt engineering, but there is a critical gap regarding the core technology stack. The role is explicitly centered on the Microsoft Power Platform (Copilot Studio, Power Apps, Power Automate), with which he has no experience. This technology stack mismatch is too significant to overcome. **Strengths:** Solutions Architecture, Python, Prompt Engineering **Critical Gaps:** Microsoft Power Platform ecosystem **Missing Required:** Microsoft Copilot Studio, Microsoft Power Apps

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This role is an excellent fit, as the candidate has proven, hands-on experience with nearly every required skill: N8N, developing agents in Python/JS, REST API integration, RAG, and prompt engineering. His recent market intelligence platform project serves as a comprehensive portfolio piece for this exact job. The resume is well-suited and requires no modification. **Strengths:** N8N and Custom Automation Flows, Development of AI Agents (Python/JS), RAG Architecture Implementation

[ANALYSIS_REPORT] **HIGH** [2.5-Pro] The candidate is a strong fit for an architect role, demonstrating deep knowledge in Python, AI/LLM solutions, RAG, and cloud fundamentals. He has practical experience building data pipelines, agents, and APIs as required. The main gap is the lack of explicit, deep experience with Kubernetes and Terraform (IaC), which are listed as mandatory. **Strengths:** Python and AI/LLM Solution Design, RAG and Embeddings Pipelines, Microservices and Event-Driven Architecture concepts **Missing Required:** IaC (Terraform), Kubernetes

[ANALYSIS_REPORT] **MEDIUM** [2.5-Pro] The candidate aligns well with the role's goal of automating business processes with AI, and his experience with Python, LangChain, and RAG is relevant. However, the requirement of a CS/Engineering degree might be an ATS hurdle, and the 1-3 years of experience could be misinterpreted by an ATS, as he has more total experience but not with a 'Software Engineer' title. The score is capped due to the risk of ATS filtering on these points. **Strengths:** Python and JavaScript Frameworks, Hands-on with Generative AI Tools (LangChain, OpenAI), Building and integrating RAG pipelines **Missing Required:** 1–3 anos de experiência em desenvolvimento de software (by title)

[ANALYSIS_REPORT] **LOW** [2.5-Pro] While the person has strong technical architecture skills, this is a senior enterprise solutions architect role requiring 8-10 years of experience in that specific function, including team leadership and pre-sales. His background does not align with the required experience in managing teams, pre-sales cycles (RFPs), or corporate-level architectural documentation. The role is less hands-on than his experience suggests. **Strengths:** Technical leadership, Development of POCs **Critical Gaps:** 8-10 years in a formal Solutions Architect role, Pre-sales and customer-facing responsibilities **Missing Required:** 8-10 anos em arquitetura de soluções, Experiência com pré-vendas

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The candidate has the required technical skills (Python, Node.js, SQL, distributed systems) for a Pre-Sales Solutions Architect role at MongoDB. However, he lacks direct experience in a customer-facing or pre-sales function, which is a core component of the job. His background is in building internal systems, not advising external clients during a sales cycle. **Strengths:** Modern scripting languages (Python, Node.js), Implementing scalable distributed systems, Translating technical concepts to business value **Missing Required:** função voltada ao cliente

[ANALYSIS_REPORT] **LOW** [2.5-Pro] This senior partner-facing role has a critical requirement of 8+ years in pre-sales with enterprise software, which the candidate does not have. While he possesses the necessary coding and distributed systems knowledge, his experience is internal-facing. The job's focus on partner enablement, channel sales, and a 50% travel requirement makes it a fundamental mismatch for his background. **Strengths:** Coding with modern languages, Experience with scalable distributed systems **Critical Gaps:** 8+ years in pre-sales with enterprise software **Missing Required:** 8+ anos de experiência em pré-vendas com software empresarial

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The score is neutral because while the candidate has demonstrated the ability to implement a core technology (OAuth 2.0/OIDC), the role requires deep, proven expertise in the entire AuthN/AuthZ domain, which is not the central theme of his resume. His experience is more generalist systems building rather than specialized security architecture. The resume should be modified to include a dedicated section on security implementations to better align with such roles. **Strengths:** Hands-on implementation of OAuth 2.0/OIDC, Systems design, Node.js/Python experience **Missing Required:** Proven expertise in API security and identity flows

[ANALYSIS_REPORT] **TOP** [2.5-Pro] The person is a very strong candidate, with a solid foundation in statistics (inferred from finance/supply chain work), practical experience with LLMs/RAG in production, and advanced Python/SQL skills. His focus on metrics, security, and data compliance aligns perfectly with the JD. The only minor gap is a lack of explicit experience with Airflow. **Strengths:** LLM/RAG in production, Scientific method (hypothesis, evaluation), Advanced Python and SQL