Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Critical frontend gap: no React, Angular, or modern frontend framework experience. While candidate has strong backend skills (Go, Python, Node.js, PostgreSQL, Docker), the JD explicitly requires full-stack with frontend frameworks. Missing 'Software Engineer' title in work history. However, consulting environment experience is a plus. To improve: add frontend project to portfolio, even if small, and emphasize API/backend work more prominently. **Strengths:** Go production experience, Node.js and Python, PostgreSQL, Docker, REST APIs, Client consulting experience **Critical Gaps:** Frontend development **Missing Required:** 3-5 years professional Software Engineer title, Frontend framework expertise

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Strong architecture mindset match but missing specific AWS enterprise tools. Candidate has infrastructure, security (OAuth 2.0), and systems thinking from Mechatronics background, but no hands-on AWS Control Tower, Organizations, or Landing Zone experience. Banking sector experience is absent. Hybrid work model in São Paulo is feasible. To improve: obtain AWS Solutions Architect certification and build small Landing Zone project. **Strengths:** Systems architecture mindset, Security/OAuth 2.0, Constraint-based engineering, Infrastructure optimization, Governance concepts **Missing Required:** AWS enterprise architecture production experience

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opencode:kimi-k2.5] Strong Python and API integration skills, with e-commerce automation background that translates to Shopify concepts. Missing explicit 8 years Python and specific high-volume transactional system experience at scale. Has OAuth and webhook architecture implicitly from job platform work. No explicit Shopify experience but e-commerce domain knowledge is present. To improve: emphasize order volume processed (40-50 orders/day currently), add explicit Python years count. **Strengths:** Python production use, API design and integration, E-commerce domain knowledge, OAuth 2.0 implementation, Webhook processing, Error handling and retry logic **Missing Required:** 8 years professional Python development experience

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The score is low due to a critical gap in the core technology required: Microsoft Azure. The role is for a senior Azure specialist, and the candidate's experience is limited to AWS fundamentals. His architectural skills are not transferable without deep platform-specific knowledge. **Strengths:** General Systems Architecture, Cost Optimization Concepts, CI/CD and Docker knowledge **Critical Gaps:** Azure proficiency **Missing Required:** Senior-level cloud engineering experience on Azure

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Excellent match for core data engineering requirements. Strong SQL skills with PostgreSQL (transferable to SQL Server/Oracle), data pipeline experience from job platform and e-commerce automation, data modeling and quality focus demonstrated through ERP data remediation (4,000+ records). Missing Azure-specific tools but has cloud fundamentals. Business-technical bridge aligns with stakeholder collaboration requirement. Hybrid in São Paulo is feasible. **Strengths:** SQL and data modeling, Data pipeline architecture, Data quality and validation, ERP data remediation, Business-technical translation, Cloud fundamentals

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Missing critical requirements: Databricks and PySpark are explicitly required, not just preferred. Bachelor's degree in Mechatronics may not pass ATS filter for 'CS or related' requirement. Big Four consulting environment is familiar but core technical stack mismatch is severe. To improve: complete Databricks certification and build migration project for portfolio. **Strengths:** Python, Data pipelines, Cloud fundamentals, Consulting environment familiarity **Missing Required:** Databricks production experience, PySpark, Bachelor's in CS/IS (ATS risk), Big Four financial institution experience

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Strong alignment with AI-first development methodology - candidate is already working this way with Claude/Gemini APIs, prompt engineering, and AI tools. Missing TypeScript explicitly and 5 years 'engineering' title. Has Node.js, PostgreSQL, AWS fundamentals, and scaling experience (1vCPU optimization). Startup environment is excellent match. To improve: add TypeScript to recent projects and quantify years of Node.js work explicitly. **Strengths:** Node.js production use, AI-first development (Claude, Gemini, OpenAI), Prompt engineering expertise, PostgreSQL, AWS, Performance optimization, Startup environment match, LLM integration experience **Missing Required:** 5 years engineering experience with title, TypeScript

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opencode:kimi-k2.5] Good architecture and infrastructure match with system design experience, OAuth 2.0 security implementation, CI/CD concepts, and GCP fundamentals. Missing microservices and serverless production experience. Fullstack requirement is gap (no frontend frameworks). End-to-end ownership aligns with founder experience. Portuguese-language role reduces competition. To improve: add microservices example to portfolio, clarify GCP project scope. **Strengths:** System architecture, Security/OAuth 2.0, CI/CD, End-to-end ownership, API design, GCP fundamentals

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Strong Go and AI infrastructure match - exactly what candidate has been building. Missing Java/JVM experience and Staff/Tech Lead title history. 50% hands-on aligns with preference. Enterprise-level team leadership (2-3 juniors) is unproven. Iron Mountain is large enterprise (weak culture fit). To improve: emphasize mentorship aspects from consulting work, add Java basics to skillset. **Strengths:** Go production expertise, AI infrastructure (LLM pipelines), Architecture design, Mentorship potential, 50% hands-on preference match **Missing Required:** Staff/Tech Lead experience level, Java or JVM language

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The score is low due to critical gaps in the required data engineering stack. The role is specifically for Google BigQuery and Apache Airflow, neither of which are in the candidate's toolkit. While he has built a custom orchestrator, this role requires expertise in a specific, off-the-shelf tool. **Strengths:** Python for data processing, Advanced SQL, Git **Critical Gaps:** Google BigQuery, Apache Airflow **Missing Required:** Data Engineer title

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Excellent operational mindset match - candidate thrives in production triage and stability focus. Strong CI/CD, Docker, automation (Go/Python/Bash), and production operations experience (e-commerce, job platform). Missing Kubernetes production and Azure (has AWS). No 'DevOps' or 'Operations' title but function is demonstrated. To improve: add Kubernetes project to portfolio, clarify production incident response experience. **Strengths:** CI/CD, Docker, Production operations, Automation scripting, Go and Python, Troubleshooting, Bash, Linux, Infrastructure optimization

[ANALYSIS_REPORT] **LOW** [2.5-Pro] The candidate is a strong systems thinker and builder, which aligns well with the DevOps philosophy. His skills in cloud, Docker, and CI/CD are relevant. The score is capped due to a missing required skill (Terraform) and the lack of a formal 'DevOps Engineer' title. **Strengths:** Systems Thinking, Docker & CI/CD, Python **Missing Required:** Terraform, DevOps Engineer title

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opencode:kimi-k2.5] Strong backend focus match - Go, Python, Node.js production experience. Feature development end-to-end demonstrated through job platform and e-commerce systems. Ownership, stability, performance optimization (1vCPU story), and scalability are all proven. Missing 'Backend Developer' or 'Software Engineer' title is ATS risk. Generic JD without specific stack details helps. To improve: lead with backend Go work, quantify scale and performance metrics. **Strengths:** Go backend production, Python backend, Node.js backend, Feature development, Component ownership, Performance optimization, Stability focus, Scalable architecture **Missing Required:** Professional backend development title

[ANALYSIS_REPORT] **HIGH** [Opencode: opencode:kimi-k2.5] Strong data engineering fundamentals match - SQL expertise, data modeling, ETL pipelines, data quality/governance, performance tuning. Microsoft SQL Server and SSRS are missing but PostgreSQL and SQL concepts are transferable. T-SQL is similar to standard SQL. Data Warehouse concepts align with data architecture work. Portuguese-language role. To improve: add MSSQL project or certification, highlight any reporting/dashboard work. **Strengths:** SQL mastery, Data modeling, ETL pipelines, Data quality, Performance tuning, PostgreSQL (transferable), Data governance

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Complete ecosystem mismatch. No Microsoft Dynamics 365, X++, C#/.NET, Power Platform, or Azure Integration Services experience. AI work is with Claude/Gemini/OpenAI, not Microsoft Copilot. 5 years D365 and certifications (PL-400, MB-500) are hard requirements. This is entirely different technical stack from candidate's expertise. To improve: not applicable - would require complete reskilling. **Critical Gaps:** Microsoft Dynamics 365 ecosystem **Missing Required:** 5 years D365 development, Microsoft certifications (PL-400, MB-500, MB-400), C#/.NET stack

[ANALYSIS_REPORT] **LOW** [2.5-Pro] This role has a critical requirement for .NET Core, a technology the candidate has no experience with. This single mismatch makes the profile unsuitable, despite some overlap in secondary skills like Python and AWS. The JD also asks for deep, specific AWS service knowledge that the candidate does not list. **Strengths:** Python, Docker, Microservices Concepts **Critical Gaps:** .NET Core **Missing Required:** Senior Developer title

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Strong supply chain domain match and Python/PostgreSQL alignment. E-commerce operations directly translate to supply chain/operations tech. However, critical frontend gap - no React or TypeScript experience. Kubernetes production missing. FastAPI is minor gap (has Python API experience). Domain expertise is standout factor but frontend requirement blocks progress. To improve: learn React basics and build small supply chain dashboard project. **Strengths:** Python, PostgreSQL, Supply chain domain expertise, Operations technology, API integration, IAM/Auth (OAuth 2.0), Docker, Security mindset **Critical Gaps:** Frontend development

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opencode:kimi-k2.5] Strong Python, JavaScript, SQL foundation for data visualization. Has authentication (OAuth 2.0), data pipelines, AWS, Linux. Missing specific visualization frameworks (Streamlit, Plotly, Dash) and specialized data pipeline tools (Kafka, Spark, Airflow). No explicit 'data engineering' title. 5 years requirement is stretch. To improve: add Streamlit or Plotly dashboard project to portfolio, highlight any visualization work from job platform. **Strengths:** Python, JavaScript, SQL, Data pipelines, Authentication/authorization, AWS, Linux, Docker, HTML/CSS **Missing Required:** 5 years data engineering or visualization experience

[ANALYSIS_REPORT] **LOW** [Opencode: opencode:kimi-k2.5] Strong architecture, GenAI, cloud, API, CI/CD alignment. Has solution design experience, LLM pipelines, mentoring potential from consulting. Missing 'Solution Architect' or 'Architect' title, enterprise-scale architecture, and microservices at scale. Client leadership at enterprise level unproven. Enterprise consulting environment has red flags. To improve: emphasize architecture decisions from job platform project, quantify system scale. **Strengths:** GenAI/LLM expertise, System architecture, Cloud infrastructure, API design, CI/CD, Data management, Mentoring potential **Missing Required:** Architect-level experience, Enterprise architecture

[ANALYSIS_REPORT] **TOP** [2.5-Pro] This job description is an almost perfect match for the candidate's recent projects, focusing on RAG, agent pipelines, and integrating various LLM APIs. The score is capped only by the non-traditional job title, which is an ATS risk. His hands-on experience with LangChain and productionizing LLM workflows makes him an ideal candidate. **Strengths:** RAG and Agent Pipelines, LLM API Integration (OpenAI, Anthropic, etc.), LangChain **Missing Required:** AI Developer title

[ANALYSIS_REPORT] **HIGH** [2.5-Pro] This role, focusing on AI solution architecture and implementation, is a strong fit for the candidate's skills and mindset. The score is capped by the ATS risks of not having a formal 'Engineer' title and potentially not meeting the '3+ years in AI' filter, as his most direct AI work is more recent. His broader systems experience is highly relevant but may be overlooked by an ATS. **Strengths:** AI Solution Architecture, Implementing scalable AI applications, Python **Missing Required:** 3+ years explicit AI experience, Engineer title

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Candidate demonstrates RAG pipeline design, LLM integration (Claude/Gemini/OpenAI APIs), workflow orchestration (custom Go orchestrator, n8n mentioned in skills), and financial services domain experience from prior roles. However, lacks TensorFlow/PyTorch/Scikit-Learn experience and formal ML model training at scale. Resume should emphasize AI pipeline production deployment and add specific mentions of data pipeline scale metrics. **Strengths:** RAG pipeline design and deployment, LLM API integration (Claude/Gemini/OpenAI), Financial services domain experience, Workflow orchestration experience **Missing Required:** 3-5 years AI/ML engineering title

[ANALYSIS_REPORT] **MEDIUM** [Opencode: opus-4-5] Candidate has Python proficiency, LLM integration experience, and production AI deployment (job platform scoring pipeline). Missing formal ML framework experience and no AI/ML title history. The role is more general than Job 1, making transferable skills more valuable. Resume should highlight the AI scoring pipeline with variance reduction metrics as ML model optimization. **Strengths:** Python proficiency, AI solution deployment to production, Data processing experience **Missing Required:** 3+ years AI/ML engineering role

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Candidate has Python experience, prompt engineering with PID-control-inspired tuning showing quantitative rigor, and LLM pipeline design. However, role requires hybrid in Florianópolis which is a geographic constraint, and demands extensive NLP/LLM production experience and ability to lead technical initiatives. Resume should emphasize the statistical validation of prompt tuning (26% to 2.9% variance). **Strengths:** Prompt engineering with statistical validation, LLM pipeline design, Python proficiency **Critical Gaps:** Hybrid Florianópolis requirement **Missing Required:** Extensive Python generative AI production experience, Technical leadership title

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-5] Candidate has self-hosted LLM experience (mentioned HuggingFace inference), PostgreSQL, Python, Linux infrastructure, and observability concepts. However, lacks 6+ years backend engineering with Python title, no OCR pipeline experience, no proven GPU infrastructure management. Critical gaps in OCR-specific document processing. Resume would need significant additions for this highly specialized role. **Strengths:** LLM API integration, PostgreSQL, Linux infrastructure, Self-hosted deployment mindset **Critical Gaps:** OCR-based document intelligence experience **Missing Required:** 6+ years backend engineering, Long-form PDF OCR pipeline experience