Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [Opencode: google/3-Flash] Hard filter violation: Role is restricted to U.S. based candidates only. Candidate is based in Brazil. **Critical Gaps:** Geographic restriction **Missing Required:** U.S. residency/work location

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5-free] Strong match on RAG, N8N, LLM orchestration, Python, and agent design. Candidate has built production RAG pipeline with statistical validation. Missing K8s production and MLflow but has custom orchestration. Degree requirement may cap score. **Strengths:** Production RAG pipeline, N8N familiarity, Multi-agent orchestration concept, Prompt engineering, Vector embeddings, Python

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5-free] Big consulting (EY) with CS degree preference and heavy Azure stack. Candidate has strong GenAI skills but missing Azure production and formal CS degree. Culture mismatch with enterprise consulting. **Strengths:** LangChain equivalent, RAG, Multi-agent architecture, Python, MCP/A2A concepts **Critical Gaps:** Big consulting culture, Azure ecosystem **Missing Required:** CS degree preferred

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5-free] Strong match on RAG, LLM APIs, Python, and conversational AI. Built custom orchestrator equivalent to LangChain. Missing C# and Azure production but has cloud deployment experience. Remote-friendly. **Strengths:** Custom LLM orchestrator, RAG pipeline, API integration, Vector search, Production deployment, Python

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5-free] Strong Python and AI architecture match. Built production systems with agent-like behavior. Missing specific LangChain/LangGraph production but has equivalent custom framework. RAG and vector DB experience present. Hybrid in SP matches location. **Strengths:** Python advanced, RAG architecture, Vector embeddings, Custom orchestration, AI observability, Cloud deployment, Sao Paulo based

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opencode:kimi-k2.5-free] Requires 4+ years software engineering title. Strong on GenAI skills but missing Flask/FastAPI production and specific vector DBs. Title gap is main blocker. **Strengths:** Python, RAG, Vector search concept, Docker, Cloud deployment **Critical Gaps:** Years of experience gate, No formal SE title **Missing Required:** 4+ anos engenharia de software

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5-free] SAP S/4HANA specialization required. Candidate has zero SAP experience. Complete domain mismatch. **Strengths:** AI automation, Process optimization **Critical Gaps:** No SAP experience whatsoever **Missing Required:** SAP S/4HANA

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5] Strong alignment on LLMs/RAG, microservices/APIs, Docker and CI/CD, but lacks required Java and explicit test automation. Adjacent DB experience (PostgreSQL) fits general familiarity, yet Kubernetes/observability are only partial. Systems-level project scale and recent AI work are positives, but ATS will penalize missing Java keywords. **Strengths:** LLMs & RAG pipelines, Microservices/APIs (Go/Node), Docker & CI/CD **Missing Required:** Java (domain), Automated testing (unit/integration/functional)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5] Onsite requirement in Bauru/SP is a hard geographic filter; candidate is São Paulo-based without indicated relocation. Skill fit on LLMs/automation is solid but irrelevant under ATS location screening. Excel/automation strengths would help only if location is met. **Strengths:** LLM experience, Automation (n8n/scripting), Excel advanced

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5-free] Candidate demonstrates strong practical experience with LLM API integration (OpenAI, Claude, Gemini), backend development in Go and Python, and database work with PostgreSQL. However, the ATS will flag the absence of the specific '2+ years backend AI Engineer' job title, missing Databricks and Kafka experience, and lack of production MCP (Model Context Protocol) knowledge. The Mechatronics degree and non-traditional trajectory won't align with EPAM's rigid consulting hiring filters. **Strengths:** LLM API integration (OpenAI, Claude, Gemini), Backend development (Go, Python), PostgreSQL/SQL databases, CI/CD pipelines, Prompt engineering **Critical Gaps:** Professional backend AI Engineer title/experience, Big consulting company culture fit **Missing Required:** 2+ years experience as backend AI Engineer, Databricks, Kafka, MCP

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5] Good match on REST APIs and OAuth/OIDC plus general agentic AI/automation, but lacks required .NET/C# backend and concrete Zendesk platform experience. Webhooks/ZAF/Sunshine are not present in the resume. Niche vendor platform keywords are likely hard filters. **Strengths:** REST APIs & OAuth/OIDC, Automation/agentic AI background, Integration mindset & CI/CD **Missing Required:** .NET/C# backend experience, Zendesk platform (AI Agents, triggers, automations)

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5] Very strong on Python, APIs, LLMs/agents, SQL and CI/CD, but ATS will not see RPA frameworks and Azure Functions keywords. Streamlit/Pandas are differentiators not present. Recent AI infra work and systems thinking align well with responsibilities. **Strengths:** Python APIs, LLM/Agents pipeline design, SQL/DB experience **Missing Required:** RPA experience, Azure Functions/workers

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5] Similar to Job 1: solid on LLMs/RAG, microservices/APIs, Docker and CI/CD but lacks required Java and explicit automated testing. DB familiarity is adjacent (PostgreSQL vs SQL Server/Oracle/Cassandra). Kubernetes/observability are partial and multi-agent framework experience is not explicit. **Strengths:** LLMs & RAG pipelines, Microservices/APIs (Go/Node), Docker & CI/CD **Missing Required:** Java (domain), Automated testing (unit/integration/functional)

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5] Excellent match for junior AI/automation: Python/Node, APIs, SQL/NoSQL, RAG and agents, plus Git and AWS basics. Resume exceeds requirements, though RPA tools are not explicitly listed. ATS will rank high despite title mismatch due to strong recent AI work. **Strengths:** Python/Node foundations, RAG and agents knowledge, Git and database experience

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5] Good conceptual/implementation match on LLMs/RAG, microservices/APIs, and security/OAuth; Docker and cost/efficiency mindset are aligned. Missing explicit Kubernetes/IaC, observability/tracing at enterprise scale, and MCP/protocol experience. LangChain experience is adjacent to LangGraph requirements. **Strengths:** Systems architecture & LLM pipeline evaluation, Microservices/APIs with OAuth/OIDC, Docker and efficiency-first engineering **Missing Required:** Kubernetes/IaC experience, Observability/tracing for LLMs/agents, MCP/protocol experience

[ANALYSIS_REPORT] **TOP** [3-pro] Strong match for Python, RPA, and Agentic AI requirements. The Candidate's experience building a custom orchestrator and market intelligence platform maps directly to 'SONIA's' needs. Lack of 'Distributed Systems' at scale is a minor gap offset by deep vertical integration experience. **Strengths:** Python, RPA/Automation, AI Agents/LLMs, System Architecture

[ANALYSIS_REPORT] **LOW** [3-pro] Enterprise-heavy role focused on governance, MLOps, and document processing within a law firm. While the Candidate has the LLM skills, the environment likely demands strict enterprise process adherence (MLOps, rigorous testing) rather than 'scrappy' builder energy. **Strengths:** LLMs, NLP, Python **Missing Required:** Graduation in Computing (Mechatronics might flag)

[ANALYSIS_REPORT] **HIGH** [3-pro] Solid match for Python, RAG, and Vector DBs. The Candidate's experience with 'single server' architecture clashes slightly with the heavy Cloud/K8s/Terraform requirements, but the core Generative AI skills are spot on. **Strengths:** RAG, Python, Vector Databases, Embeddings

[ANALYSIS_REPORT] **MEDIUM** [3-pro] Good match for Python, GenAI, and low-code (n8n) integration. The Candidate's background fits the 'transversal' nature of the role. Major gap is the Azure-specific stack and Streamlit (Candidate prefers vanilla/Go), but these are learnable. **Strengths:** Python, GenAI, n8n, Agents

[ANALYSIS_REPORT] **TOP** [3-pro] Excellent cultural and technical fit. The role asks for 'Vibe Coding', n8n, and a 'builder' profile to prototype fast. This aligns perfectly with the Candidate's self-description. 'DevOps' requirement is met by his Linux/Docker/Self-hosting experience. **Strengths:** n8n, Vibe Coding / Prototyping, LLM Integration, Linux/Ops

[ANALYSIS_REPORT] **HIGH** [3-pro] Strong alignment on specific AI models (Gemini/Claude) and n8n. Olist is a data-driven environment which fits the Candidate's background in supply chain/finance analytics. Title 'Analyst' is a downgrade but the scope seems technical. **Strengths:** Claude/Gemini APIs, n8n, Data Analysis, Process Automation

[ANALYSIS_REPORT] **LOW** [3-pro] Legacy chatbot role disguised as modern AI. Requires deep IBM Watson Assistant expertise (Actions/Entities) and Node.js. The Candidate focuses on modern LLMs/Agents, not closed-source legacy NLP stacks. **Strengths:** Node.js, Prompt Engineering **Critical Gaps:** Specific IBM stack requirement **Missing Required:** IBM Watson Assistant

[ANALYSIS_REPORT] **LOW** [3-pro] Heavily focused on Microsoft Power Platform (Copilot Studio, Power Automate). The Candidate advocates for 'no bloat of abstraction' and code-first solutions, which is philosophically opposed to this low-code enterprise stack. **Strengths:** Agents, Automation logic **Critical Gaps:** Ecosystem mismatch (Microsoft Low-Code vs Code-First) **Missing Required:** Copilot Studio

[ANALYSIS_REPORT] **LOW** [3-pro] Hard technical disqualification: The role requires C#/.NET Core. The Candidate is a Go/Python/Node developer. No overlap in primary programming language. **Strengths:** n8n, OpenAI API **Critical Gaps:** Wrong programming language **Missing Required:** .NET experience, C#

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5] Strong systems/architecture and business-tech translation, but role requires deep Salesforce platform/CPQ and RevOps solutioning. Candidate lacks Salesforce certifications and hands-on architecture depth there. Communication and leadership fit, but tech stack mismatch. **Strengths:** Architecture leadership and stakeholder translation, Process automation mindset, Data quality and validation logic experience **Missing Required:** Salesforce platform expertise, CPQ solution architecture