Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The candidate is a poor fit for this role's specific tech stack. It requires a Fullstack Engineer with expertise in React/Angular/Vue and NodeJS/Go/Python. While he knows Go and Python, the role seems to have a strong frontend focus, and his frontend experience is Vanilla JS, not a modern framework like React. This framework gap significantly lowers his score. **Strengths:** Back-end development (Go, Python), REST API Design, Cloud deployment (AWS) **Critical Gaps:** Modern frontend framework (React, Angular, Vue)

[ANALYSIS_REPORT] **MEDIUM** [2.5-Pro] This role is a duplicate. The candidate's skills in AI/ML, Python, and architecture are a good match, but he lacks the required Snowflake experience and does not meet the 8+ years of experience in an architect role. The ATS score is capped at 70 due to these missing requirements. **Strengths:** AI/ML Architecture, LangChain, Python **Missing Required:** Snowflake (Cortex, Vector Search), 8+ years of professional experience in AI/ML architecture

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person demonstrates strong architecture, automation, and AI solution experience, with direct client-facing and technical leadership. However, there is no explicit record of holding a 'Principal Architect' or 'Technical Director' title, and no evidence of formal Agile/SDLC process leadership or AWS certification. Some required skills are inferred but not directly matched, and the lack of brand-name consultancy or deep enterprise experience is a minor gap. **Strengths:** AI systems architecture, client-facing technical leadership, mentoring and team building **Missing Required:** Principal Architect/Technical Director title (explicit), formal experience as primary technical lead at account/business unit level

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT4.1] The person has strong distributed systems, AI agent, and orchestration experience, with hands-on LLM pipeline and automation work. However, there is no direct experience with LangGraph, CrewAI, or Swarm, and no explicit pre-sales or Databricks background. The lack of formal agent framework experience and cloud certifications are minor gaps, but the core requirements are met through adjacent and inferred skills. **Strengths:** LLM pipeline design, distributed systems, AI automation

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Hard filter: This is an Architecture Coordinator role for building/construction design, not software architecture. JD requires ArchiCAD, architectural drawings, building permits approval, and construction project coordination. Complete domain mismatch. **Critical Gaps:** Architecture domain (buildings, not software) **Missing Required:** ArchiCAD proficiency, Architectural project experience, Building construction domain

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Hard filter: This is building/construction Architecture Analyst at Shopee logistics. JD requires AutoCAD, civil engineering projects, PPCI approvals, construction layouts for Hubs/Fulfillment centers. Complete domain mismatch - not software. **Critical Gaps:** Architecture domain (buildings/logistics, not software) **Missing Required:** AutoCAD, Civil/architectural project experience, Construction domain

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person has strong AI architecture, automation, and Python/LLM experience, but lacks a CS degree and does not meet the 7+ years of Python/LLM framework experience as explicitly required. There is no direct experience with Streamlit/Gradio, and container orchestration is present but not at the scale described. The resume demonstrates adjacent skills and strong systems thinking, but critical gaps in formal education and explicit years of experience cap the score. **Strengths:** AI systems architecture, automation, cloud and containerization **Missing Required:** formal CS/AI degree, explicit 7+ years Python/LLM

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Moderate match for Junior Solutions Architect at Claranet. Candidate has systems integration, API concepts, but missing formal pre-sales experience, cloud certifications, and architecture documentation practices. JD is junior-level which is positive for non-traditional background. **Strengths:** Systems integration experience, API understanding, Technical documentation, Business-tech translation

[ANALYSIS_REPORT] **LOW** [Copilot: GPT4.1] The person has no experience with Azure Databricks, Power BI, or the Microsoft analytics stack, and lacks deep big data/ETL pipeline experience. There is no evidence of working with Spark, PySpark, or Azure Data Factory, and the resume does not mention any Microsoft ecosystem work. These are critical gaps for this highly specialized analytics architect role. **Strengths:** SQL, data architecture, automation **Critical Gaps:** no Microsoft analytics stack experience, no big data/ETL pipeline experience **Missing Required:** Azure Databricks expertise, Power BI, Delta Lake

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Poor match for Software Architect I at Stefanini. JD requires Java Spring, Angular, PHP legacy migration, microservices architecture, JWT/OAuth2 implementation at enterprise level. Candidate has OAuth2 and systems thinking but missing Java/Angular stack entirely. **Strengths:** OAuth2/OIDC implementation, PostgreSQL, Git, Clean Code concepts **Critical Gaps:** Java Spring ecosystem, Angular frontend **Missing Required:** Java Spring Boot expertise, Angular experience, Microservices migration

[ANALYSIS_REPORT] **LOW** [Copilot: GPT4.1] The person has no experience with Rhino3D, Vectorworks, or architectural design workflows. The resume is entirely focused on systems, automation, and AI, with no evidence of CAD or architecture domain expertise. This is a critical domain gap. **Critical Gaps:** completely different domain (architecture/CAD) **Missing Required:** Rhino3D, Vectorworks

[ANALYSIS_REPORT] **LOW** [3-pro] ATS detects profound mismatch in core hard skills: SAP NetWeaver/BASIS/HANA on AWS are non-negotiable requirements, whereas Candidate brings generic ERP logic (TOTVS) and general cloud knowledge. The 'Architect' title matches, but the domain (SAP Infrastructure) is completely distinct from the Candidate's software/AI focus. Recency of relevant ERP work is also low (7+ years ago). **Strengths:** Architecture experience, Automation mindset, Migration concepts **Critical Gaps:** Deep SAP infrastructure expertise, SAP specific certifications **Missing Required:** SAP S/4HANA, SAP ECC support

[ANALYSIS_REPORT] **LOW** [3-pro] Role is heavily focused on Brazilian public sector procurement law (Lei 14.133) and tender analysis, which is a legal/administrative domain not present in the Candidate's profile. While the Candidate bridges business and tech, they lack the specific government sales machinery experience required here. **Strengths:** Technical writing, Bridging commercial and technical **Critical Gaps:** Public sector procurement legal framework, Government sales platforms **Missing Required:** Nova Lei de Licitações

[ANALYSIS_REPORT] **LOW** [3-pro] Job requires deep expertise in Microsoft Power Platform (Low-code), whereas Candidate is a 'first principles' engineer who builds custom binary orchestrators in Go. While the 'Architect' level matches, the philosophical and tooling mismatch is severe (Low-code vs. High-code/Metal). **Strengths:** System Architecture, Business Logic, Automation **Critical Gaps:** Power Platform ecosystem specialization **Missing Required:** Power Platform architecture

[ANALYSIS_REPORT] **MEDIUM** [3-pro] Strong match on 'Data & AI Architect' title and the blend of pre-sales/business alignment which Candidate excels at. However, the requirement is strictly Microsoft Azure stack (Synapse, ADF), while Candidate is open-stack/Linux/Go. The 'Consulting' aspect fits the Candidate's background. **Strengths:** AI Strategy, Business-Tech Bridge, Data Architecture **Critical Gaps:** Azure ecosystem depth **Missing Required:** Microsoft Azure certifications

[ANALYSIS_REPORT] **LOW** [3-pro] Candidate has excellent Supply Chain domain knowledge (S&OP, Demand Forecasting) and ERP experience (TOTVS), but the role demands SAP MM/SD specifically. The domain fit is high, but the tool fit is low. ATS will punish the lack of SAP keywords. **Strengths:** Supply Chain processes, Demand Forecasting, ERP logic understanding **Critical Gaps:** Specific SAP module configuration experience **Missing Required:** Sólida experiência no módulo MM

[ANALYSIS_REPORT] **LOW** [3-pro] Role is focused on Power BI and Snowflake visualization architecture. Candidate works with raw data, SQL, and backend logic, not front-end BI dashboarding tools like Power BI. Mismatch in layer of the stack (Visualization vs. Backend/Logic). **Strengths:** Data Modeling, SQL, Business Logic **Critical Gaps:** Enterprise BI tool expertise **Missing Required:** Power BI corporativo

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT4.1] The person has strong distributed systems, LLM, and AI agent experience, with hands-on orchestration and automation. There is no direct experience with LangGraph, CrewAI, or Swarm, and no explicit pre-sales or Databricks background, but the core requirements are met through adjacent and inferred skills. The lack of formal agent framework experience and cloud certifications are minor gaps. **Strengths:** LLM pipeline design, distributed systems, AI automation

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person has strong DevOps, automation, and platform engineering experience, with deep CI/CD, cloud, and scripting skills. However, there is no direct experience with Kubernetes at scale, Backstage.io, or FinOps, and the resume lacks explicit experience in FinTech or highly regulated environments. The core requirements are met through adjacent and inferred skills, but some nice-to-haves are missing. **Strengths:** automation, CI/CD, cloud infrastructure

[ANALYSIS_REPORT] **TOP** [3-pro] Excellent match. Radix works with industrial/engineering clients (Candidate has Mechatronics degree). Role requires 'Technical Leadership in AI/GenAI', Python, and architecture. Candidate's recent 'Market Intelligence Platform' is a perfect portfolio piece for this. The 'Engineering background' is a major plus here. **Strengths:** Mechatronics background (Industry fit), End-to-end GenAI implementation, Technical Leadership, Python/Architecture

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] The person has strong Azure, automation, and platform engineering experience, with deep scripting and CI/CD skills. However, there is no direct experience with Microsoft Foundry, Agent 365, or advanced telemetry tools, and the resume lacks explicit experience with Databricks, Snowflake, or Dataiku. The core requirements are met through adjacent and inferred skills, but some nice-to-haves are missing. **Strengths:** Azure platform engineering, automation, CI/CD

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT4.1] The person has strong MLOps, platform engineering, and automation experience, with deep knowledge of Kubernetes, CI/CD, and distributed systems. There is no direct experience with Mesos, GPU scheduling, or Java/Rust/C++ for high-performance services, but the core requirements are met through adjacent and inferred skills. The lack of explicit experience with Golden Path, eBPF, or cost optimization is a minor gap. **Strengths:** MLOps, Kubernetes, automation

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT4.1] The person has strong MLOps, platform engineering, and automation experience, with deep knowledge of Kubernetes, CI/CD, and distributed systems. There is no direct experience with Mesos, GPU scheduling, or Java/Rust/C++ for high-performance services, but the core requirements are met through adjacent and inferred skills. The lack of explicit experience with Golden Path, eBPF, or cost optimization is a minor gap. **Strengths:** MLOps, Kubernetes, automation

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT5.1] The ATS sees a solid match on general infrastructure engineering: Linux, Docker, Go/Node/Python, CI/CD, and building a production GenAI-adjacent platform on constrained hardware. However, there are gaps against the preferred stack (AWS/Azure/GCP depth, Terraform/CloudFormation, Ansible/Puppet/Chef, Prometheus/Grafana/ELK, Kubernetes). Non-standard titles and limited explicit cloud tooling experience keep the score in the low-60s. **Strengths:** Proven design and operation of a production web/infrastructure stack on a very small server, Strong Go/Node/Python, Linux, Docker and CI/CD experience, GenAI product exposure and ability to bridge business and engineering

[ANALYSIS_REPORT] **MEDIUM** [3-pro] Role is 'AI Platform Specialist' with heavy Databricks/MLOps focus. Candidate has built AI platforms (custom), but lacks the enterprise Databricks ecosystem experience. The 'Platform Mindset' is a strong match, but the toolset is different. **Strengths:** AI Platform Architecture, MLOps concepts, Automation, Cost control **Critical Gaps:** Databricks ecosystem **Missing Required:** Databricks em produção