Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role requires solid SAP HANA experience including SQLScript, Stored Procedures, Table Functions, Calculation Views, XS Classic/Advanced, XSJS, OData, and SAP HANA security. Candidate has zero SAP experience. Additionally requires Spanish at intermediate level, which candidate does not list. This is a deeply specialized SAP consulting role with no overlap with candidate's technology stack. No resume modifications can bridge this gap. **Strengths:** Database experience (PostgreSQL/SQLite), API integration experience **Critical Gaps:** SAP HANA — entirely different technology ecosystem **Missing Required:** SAP HANA solid experience, SAP HANA modeling and development, Spanish intermediate

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will like the AI-accelerated “builder” profile: shipped a production platform end-to-end, orchestrator, LLM scoring/prompt tuning, infra + web delivery. The main ATS penalty is lack of explicit “Claude Code” (tool-specific) and the non-traditional job titles, which many systems down-rank. To improve: add a dedicated “AI-assisted development workflow” section naming Claude Code (if used), repo links, and quantify multi-file refactors/tests/deploys. **Strengths:** LLM/prompt pipeline design + validation, Full-stack delivery (backend + web + infra), Specification/translation skill (business-to-technical) **Missing Required:** 5+ years professional software development (ATS may not credit titles cleanly)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will treat this as a front-end tech lead role (React/Angular, design systems, micro-frontends, accessibility) and the resume does not show those core deliverables. Vanilla JS and web shipping helps, but it is not evidence of React architecture leadership, WCAG/ARIA, or module federation. To improve: only pursue if there is real React/Angular portfolio; otherwise this is a mismatch. **Strengths:** Web performance mindset, CI/CD + Git familiarity, Systems thinking **Critical Gaps:** Front-end tech lead (React/Angular) experience **Missing Required:** Previous experience as a tech lead focused on front-end development

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will match Node.js/backend work (Node + LLM integrations + scraping + production delivery) and will like finance-domain exposure. The weakness is “solid cloud provider” depth plus several broad requirements (Java/crypto/design systems) that aren’t evidenced as core strengths. To improve: add a clear Node.js production section (APIs, auth, caching, security practices), plus any AWS services actually used (Lambda, IAM, S3, CloudWatch). **Strengths:** Node.js + automation/LLM integrations, Backend/API systems thinking, Finance/markets context **Missing Required:** Solid experience with at least one cloud provider (AWS/Azure/GCP)

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will strongly match prompt engineering + validation logic + LLM API usage and will infer extraction/classification ability from the scoring pipeline work. The main deduction is the explicit “5+ years with LLM-based systems,” which is unlikely to be credited given recency, and the “Data Scientist” label vs engineering-style portfolio. To improve: reframe as “LLM extraction/structured output” work with examples (schemas, evals, error analysis) and quantify accuracy gains with datasets. **Strengths:** Prompt design + validation/evals, Python + LLM APIs, Mapping unstructured text to structured signals **Missing Required:** 5+ years with LLM-based systems and prompt engineering

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will recognize LLM API experience, LangChain/RAG familiarity, SQL, and production deployment on Linux, which aligns with agent building at a high level. However, this JD is Python-first (FastAPI/Flask) and expects ML/data tooling (Pandas/TensorFlow/Fastai) plus NoSQL, which are not evidenced. To improve: only apply after adding a concrete FastAPI agent service project with tests, evals, and deployment notes. **Strengths:** LLM APIs (Claude/Gemini/OpenAI), RAG/LangChain familiarity, Production deployment + Linux **Missing Required:** Strong Python (FastAPI/Flask), ML/data libraries experience, NoSQL (MongoDB)

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This role requires deep Microsoft Dynamics 365 and Customer Insights (CDP) experience, specifically with at least 2 projects using Customer Insights – Data. Candidate has zero Microsoft Dynamics experience. The role involves Microsoft-specific ETL, Dataflows, and customer data unification within the Dynamics ecosystem. While candidate has general data pipeline and database experience, this is an entirely different platform specialization. No resume modifications can bridge zero Dynamics experience. **Strengths:** Data pipeline experience, Database experience, ETL conceptual understanding **Critical Gaps:** Microsoft Dynamics ecosystem — entirely different platform **Missing Required:** 2+ projects with Customer Insights – Data, Microsoft Dynamics 365 development, Microsoft ecosystem integrations

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will like the AI-accelerated builder profile, full-stack delivery, infra + backend ownership, and disciplined human-in-the-loop review language (direct match to the JD). The main penalty is that “deep GitHub Copilot as primary environment” is implied but not explicitly demonstrated, and job titles are non-traditional. To improve: add a “Copilot-driven workflow” section with examples (multi-file refactors, tests, PR discipline) and normalize titles toward software engineering. **Strengths:** AI-first development workflows, Full-stack + infra delivery, Specification/translation skill **Missing Required:** 5+ years professional software development (ATS may title-gate)

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] This is a Frontend Engineer role requiring advanced React, HTML5, CSS3, TypeScript, and responsive UI development. Candidate's experience is overwhelmingly backend/systems — Go, Python, PostgreSQL, CLI tools. The 'Vanilla JS' on the portfolio website is not equivalent to React component architecture. While candidate has some JavaScript/Node.js, the role requires deep frontend specialization that is entirely absent from the resume. The JD title even says 'Front-End' explicitly. **Strengths:** JavaScript knowledge (basic), API integration experience, Docker **Critical Gaps:** Frontend development — candidate is backend/systems only **Missing Required:** React advanced experience, HTML5/CSS3 advanced, TypeScript, Frontend development experience

[ANALYSIS_REPORT] **LOW** [Opencode: opus-4-6] Hard filter: this is an internship (estagiário) requiring active university enrollment with graduation from December 2026 onwards. Candidate graduated in 2014 and is a 33-year-old professional with 12+ years of experience. Additionally requires presencial work in Sao Paulo 6h/day for 12 months. This is a demographic filter — the role is for current university students only. **Strengths:** Python proficiency, Linux knowledge, Cloud fundamentals **Critical Gaps:** Student-only internship — candidate is not a student **Missing Required:** Active university enrollment, Graduation date from Dec 2026+

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will match strong SQL/Python, systems/data thinking, and the “business-to-technical translator” profile that Solutions Engineer roles value. The main gap is Snowflake-specific data warehouse positioning and explicit presales cycle experience (POCs, demos, objections). To improve: add a presales-style portfolio narrative (problem → demo → value → rollout) and any Snowflake/warehouse exposure or equivalent large-scale analytics stack. **Strengths:** SQL analytics + data remediation, Executive/technical translation, Python + automation mindset **Missing Required:** Hands-on expertise presenting Snowflake technology (or direct equivalent)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will treat this as React-first fullstack with strong UX emphasis, and the resume does not show React/UI engineering as a primary competency. Backend/infrastructure strengths won’t compensate because the JD prioritizes frontend quality, testing, and UX craft. To improve: only apply if there is a real React portfolio with shipped UI, tests, and accessibility/responsive work. **Strengths:** Security/performance mindset, CI/CD + infrastructure fundamentals, Backend systems thinking **Critical Gaps:** Frontend-heavy fullstack (React) experience **Missing Required:** Proficiency in React, Frontend emphasis on UX

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will see Python/SQL/Linux strengths, but this role is Azure-first Data DevOps with Spark/Kafka + IaC (Terraform/Ansible) and data engineering tenure. “AWS fundamentals” and general automation won’t be treated as equivalent to deep Azure landing + data platform ops. To improve: only apply after adding Azure hands-on (pipelines, networking, monitoring) plus Spark/Kafka/Airflow and Terraform project evidence. **Strengths:** Python automation, SQL + data quality mindset, Linux systems thinking **Critical Gaps:** Deep Azure data-infra leadership **Missing Required:** Extensive Azure experience, Spark/Kafka stack, Infrastructure as Code (Terraform/Ansible), 5+ years data engineering or related

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.2] ATS will strongly match AI-first workflow language, full-stack delivery, infra + backend ownership, and disciplined validation practices. The main penalty is missing explicit “Copilot as primary environment” proof and potential title-gating on the 5+ years requirement. To improve: add Copilot-driven multi-file examples, testing/CI signals, and normalize experience headings toward software engineering deliverables. **Strengths:** AI-assisted engineering discipline, End-to-end systems shipping, Strong architecture + constraints mindset **Missing Required:** 5+ years professional software development (ATS may title-gate)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT4.1] The candidate lacks direct experience with core banking systems, regulatory environments (BACEN, FEBRABAN), and specific financial modules (Investimentos Renda Fixa, Conta PJ, Boletos). While there is some financial and automation background, critical gaps in domain expertise and regulatory compliance are present. To improve, the candidate should gain hands-on experience with core banking platforms and regulatory standards. **Strengths:** automation, API integrations, system architecture **Critical Gaps:** deep core banking expertise, regulatory adherence **Missing Required:** core banking experience, financial regulatory knowledge

[ANALYSIS_REPORT] **HIGH** [Copilot: GPT5.2] ATS will match senior backend delivery (Go, SQL/PostgreSQL, Linux, OAuth/SSO, production deployment) and will like bilingual fit (English + Portuguese) and remote readiness. The essential gaps are .NET/C# plus Terraform/Kubernetes, which are called out as must-have or must-learn. To improve: explicitly state active learning plan + a small shipped C#/.NET API and Terraform/K8s deployment example to remove the “unknown stack” risk. **Strengths:** Backend systems shipped in production (Go), Auth/SSO/OAuth implementation, Remote + bilingual collaboration **Missing Required:** Familiarity or willingness to learn .NET/C#, Terraform, Kubernetes (must be credibly evidenced)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will recognize Go + PostgreSQL + Linux + REST and infer some systems capability from the orchestrator work. But this is an enterprise OSS/dev role expecting Java, microservices, Kafka, gRPC/gNMI, NoSQL, and query tuning, which are not evidenced and are treated as required. To improve: only apply if Java + distributed systems tooling (Kafka/gRPC) can be demonstrated via recent projects and the resume is rewritten toward “software developer” tenure. **Strengths:** Go production delivery, PostgreSQL/SQL competence, Linux + deployment mindset **Missing Required:** 5+ years as a software developer (explicit), Java experience, Kafka experience, NoSQL experience

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT4.1] Strong match for Go, Python, automation, CI/CD, and distributed systems. Lacks direct experience with Java/Kotlin, some cloud specifics (serverless, Kubernetes), and large-scale banking infra. To improve, highlight any experience with containers, cloud, and structured team environments. **Strengths:** Go expertise, automation, distributed systems

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will like Go/Python, API building, and a meticulous/ownership narrative, which fits the behavioral profile. However, the JD requires practical blockchain knowledge plus token/contract development, and that is a tool/domain-specific requirement that cannot be inferred from general backend work. To improve: only apply after shipping at least one on-chain contract + token project with tests, audits/linting, and mainnet/testnet deployment notes. **Strengths:** Go/Python backend capability, API/service ownership mindset, Comfort with ambiguity/hypothesis-driven work **Critical Gaps:** Practical blockchain + smart contract development **Missing Required:** Practical blockchain knowledge, Token creation and on-chain contract development

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.2] ATS will see strong systems/infrastructure thinking, Linux, automation, and some AWS familiarity, but this role is deep AWS Landing Zone + Control Tower + governance/security/networking for banking. “AWS fundamentals” is not equivalent to multi-account landing zone architecture and compliance tooling, so the gap is treated as critical. To improve: only apply with direct Landing Zone/Control Tower experience (or a detailed homelab equivalent) plus Terraform/IaC and security controls evidence. **Strengths:** Infrastructure optimization mindset, Security-conscious engineering language, Automation/constraint-based architecture **Critical Gaps:** Deep AWS landing zone + banking governance/compliance architecture **Missing Required:** AWS Landing Zone/Control Tower governance foundation (deep)

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.1] The candidate matches core Python, SQL, and data pipeline work and has experience designing automated scoring and reporting systems, which aligns with marketing analytics pipelines. However, there is no demonstrated Snowflake, dbt, or Dagster/Airflow experience, and marketing data platform exposure is only indirect via e-commerce. To improve, the candidate should add concrete projects or training using Snowflake, dbt, and an orchestrator plus explicitly describe any marketing/CRM data work. **Strengths:** Python-based data and automation work, Strong SQL and PostgreSQL experience, Production automation and CI/CD mindset **Missing Required:** Significant Snowflake experience, dbt for transformations, Dagster or Airflow orchestration

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.1] The candidate has strong backend automation experience, Python skills, SQL databases, Docker, CI/CD, and deep supply chain domain knowledge that map well to data-backed supply chain solutions. However, there is no explicit React/Vue frontend, Kubernetes, or named Python web frameworks and limited evidence of cloud-native monitoring tooling. Improving this match would require adding a small public FastAPI/Flask service, basic React/Vue work, and clarifying any Kubernetes or cloud deployment experience. **Strengths:** Supply chain and operations domain expertise, Backend automation and data workflows, CI/CD and Git-based collaboration experience **Missing Required:** React or Vue frontend experience, Kubernetes orchestration experience

[ANALYSIS_REPORT] **LOW** [Copilot: GPT5.1] The candidate brings Python, SQL, and ETL-style work but lacks any explicit Big Data, PySpark, Kafka, or AWS Big Data tooling experience that are central to this role. The position expects large-scale MPP pipelines and Big Data project history, which the resume does not show. To move closer to fit, the candidate would need real projects with Spark or PySpark, Kafka, and at least one AWS Big Data stack (e.g., EMR, Kinesis, Redshift). **Strengths:** Solid Python and SQL foundation, Experience cleaning and structuring operational data, Process automation mindset **Critical Gaps:** End-to-end Big Data architecture and processing at scale **Missing Required:** Hands-on Big Data project experience, PySpark for distributed processing, AWS Big Data tools (EMR, Kinesis, Redshift, Glue), Kafka for streaming pipelines

[ANALYSIS_REPORT] **MEDIUM** [Copilot: GPT5.1] The candidate has Python, SQL, automation, web scraping, cloud fundamentals, and experience designing data flows that resemble ETL/ELT, which align with this data engineer role. However, there is no explicit Big Data environment experience, Airflow/Dagster orchestration, or geospatial/urban analytics background. To improve fit, the candidate should highlight any cloud-hosted pipelines, add a basic Airflow/Dagster project, and, if possible, a small geospatial or mapping data project. **Strengths:** Python-based data manipulation experience, Automation and monitoring mindset for pipelines, General cloud familiarity and scraping experience **Missing Required:** Experience running pipelines in Big Data environments, Airflow or Dagster orchestration

[ANALYSIS_REPORT] **TOP** [Copilot: GPT5.1] The candidate strongly matches LLM pipeline design, LangChain/RAG experience, CI/CD, and production systems delivery, which aligns with building AI agents and conversational systems. However, the resume does not yet show 3+ years of production LLM agent work, specific Python web frameworks, ML libraries, or MongoDB experience. Raising the match would require emphasizing Python-based agent work, adding FastAPI/Flask projects, and demonstrating experience with at least one ML library and a NoSQL store. **Strengths:** Deep LLM pipeline and prompt engineering experience, Hands-on RAG and LangChain-style tooling, Proven end-to-end delivery of AI-powered production systems **Missing Required:** 3+ years production LLM-based agents and conversational applications