Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Pro] Candidate is DISQUALIFIED due to a hard location mismatch (role is hybrid in Brasília). Despite an impressive trajectory and proven ability to master complex AI systems from scratch, there is a critical gap in the required core technology stack (Google Cloud Platform). The candidate's experience is in self-hosted/on-premise AI and AWS basics, not the specified GCP ecosystem (BigQuery, Vertex AI). **⚠️ Critical Gaps:** - Direct experience with the Google Cloud Platform (GCP) ecosystem is required and entirely absent. **✅ Strengths:** - Proven rapid learner with deep, hands-on experience building and deploying complex AI (LLM) and automation systems from the ground up. - Strong systems architecture background, bridging business needs (finance, supply chain) with technical infrastructure. - Intentional career trajectory moving progressively towards advanced technical and AI-focused roles. **❌ Missing Required:** Google Cloud Platform (GCP), BigQuery, Vertex AI, Dataflow

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5] Strong architecture and Python experience align well, but missing Azure and front-end (React/Next.js) expertise are notable gaps; fast-learner profile suggests quick upskilling potential. **⚠️ Critical Gaps:** - Azure - React - Next.js **✅ Strengths:** - Python proficiency - Systems architecture and design - Docker/Terraform with CI/CD **❌ Missing Required:** Azure, React, Next.js

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] Candidate is a strong architect and AI infrastructure expert with proven automation skills in Python and a remarkable ability to self-teach complex technologies. However, there is a critical gap in direct experience with the required cloud platforms (Azure, Google Workspace, Intune), which are central to this 'Modern Work' role. **⚠️ Critical Gaps:** - Lack of hands-on experience with core required cloud platforms: Azure, Google Workspace, and Intune. **✅ Strengths:** - Deep AI Infrastructure Experience (Self-hosted LLMs) - Proven Systems Architecture & Automation (Python) - Exceptional 'Fast Learner' and problem-solver **❌ Missing Required:** Azure, Google Workspace, Intune, Entra ID

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems architecture, supply-chain domain knowledge (JIT, procurement) and data/analytics background (Python, Pandas, SQL, optimization/algorithms) indicate high ability to translate business logic to technical design and learn product specifics quickly; lacking hands-on experience with commercial supply-planning platforms and full lifecycle implementations reduces an otherwise very good fit. **⚠️ Critical Gaps:** - No demonstrated hands-on experience implementing one or more commercial supply-planning products (this is explicitly required and is blocking for immediate plug-and-play delivery on o9 engagements) **✅ Strengths:** - Deep systems architecture and automation experience (metal-up infrastructure, self-hosted AI clusters) - Strong data/analytics and modeling skills (Python, Pandas, algorithmic/quantitative background) - Direct supply-chain domain expertise (JIT systems, procurement, ERP-related work) **❌ Missing Required:** Direct experience implementing supply planning products (o9 or equivalent) in production customer environments, Documented full lifecycle implementation of supply chain planning solutions (including SIT/UAT and go-live) on an enterprise planning product

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong systems architect with highly relevant, modern AI infrastructure experience (self-hosted LLMs) that directly maps to the job's focus on generative AI and chatbots. The profile demonstrates a clear trajectory towards this type of role. However, the complete lack of JAVA, a primary required language, presents a critical skill gap that prevents a higher score. **⚠️ Critical Gaps:** - JAVA **✅ Strengths:** - Systems Architecture ('metal-up' design and implementation) - Deep AI Infrastructure experience (self-hosted LLMs) - Proven automation and production system design (Python, SQL, JIT Systems) **❌ Missing Required:** Watson, Google Cloud

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] O candidato é um forte Arquiteto de Soluções com experiência comprovada em projetar e construir sistemas técnicos complexos, o que se alinha perfeitamente com o requisito principal. No entanto, existem lacunas significativas nas habilidades comerciais, como Estratégia de Preços e experiência recente em Negociações, tornando-o um forte ajuste técnico, mas mais fraco no lado comercial para uma função voltada para o cliente. **✅ Strengths:** - Arquitetura de Soluções de ponta a ponta (demonstrada com sistema JIT e clusters de IA) - Profunda experiência técnica em Python, Infraestrutura e Automação - Capacidade comprovada de aprendizado rápido e aplicação de tecnologias emergentes (Fast Learner) **❌ Missing Required:** Estratégia de Preços e Comercial, Negociações (experiência recente)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-4.1] The candidate is a strong systems architect with deep experience in automation, AI, and cloud basics, but lacks direct .NET/C# and Azure AI Services expertise, which are critical for this role. Their Python, Docker, and AI infrastructure skills are highly relevant, and their leadership and architecture background are strong matches. However, the absence of hands-on .NET, C#, and Azure AI Vision experience is a significant gap for this position. **⚠️ Critical Gaps:** - C#/.NET hands-on development - Azure AI Vision/Document Intelligence - Enterprise-grade Azure cloud-native architecture **✅ Strengths:** - AI infrastructure and automation - Systems architecture and integration - Leadership and technical mentorship **❌ Missing Required:** Strong proficiency in .NET and C#, Hands-on experience with Azure AI Vision and OpenAI Service, Experience with Azure platform services (App Services, Service Bus, Cosmos DB, SQL), Angular/SSRS integration experience

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a talented systems architect with deep experience in building automated, production-grade systems from scratch. However, his expertise lies in a custom/open-source stack (Python, Docker, self-hosted AI), which is critically misaligned with the job's focus on the Microsoft 365, Power Platform, and Azure ecosystem. While he is a proven fast learner, the gap in specific tooling and platform experience is too significant. **⚠️ Critical Gaps:** - Experience is in custom/open-source stacks (Python, Docker, local LLMs) versus the required Microsoft ecosystem (M365, Power Platform). - Lacks any demonstrated experience in Microsoft-specific administration, tenant migrations, or the M365 security suite. **✅ Strengths:** - Proven ability to architect and build complex, automated systems from the ground up. - Strong problem-solving and rapid self-teaching capabilities in complex domains (AI, Quant Finance). - Understands core infrastructure, automation, and security concepts that are transferable. **❌ Missing Required:** Power Platform (Power BI, Power Automate, Power Apps), Microsoft 365 administration (Exchange, SharePoint, Teams), Office 365 migration experience (from G Suite, file servers, etc.), Microsoft tenant unification strategy

[ANALYSIS_REPORT] **STRONG_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong expertise in solution architecture, infrastructure, automation, and integration, with hands-on experience in cloud basics, containers, security, and DevOps practices. While advanced cloud (AWS/Azure/GCP) and commercial pre-sales experience are not explicitly detailed, the candidate's rapid learning, system-building track record, and technical breadth suggest high adaptability. Minor gaps exist in specific cloud depth, FinOps/governance, and commercial proposal experience, but overall match is strong for a senior architect role. **✅ Strengths:** - Arquitetura de soluções e integração - Automação e infraestrutura - Experiência prática em segurança e DevOps **❌ Missing Required:** Cloud (AWS/Azure/GCP) avançado, Ferramentas de modelagem de arquitetura

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong architectural foundation with proven system design and Python/AI experience, but lacks specific NLP/LLM production expertise and cloud-native microservices depth. Candidate demonstrates fast learner profile with self-hosted LLM experiments and full-stack automation systems. Missing formal MLOps pipeline experience and enterprise-scale API/microservices architecture, though foundational skills are present. **✅ Strengths:** - System Architecture & End-to-End Design: Proven track record building production-grade automated systems from scratch (JIT inventory with >95% uptime, zero manual maintenance) - Python & Automation Expertise: Strong Python skills with Pandas/NumPy, shell scripting, and infrastructure automation (Docker, Terraform, CI/CD pipelines) - AI Infrastructure & Self-Learning: Hands-on experience self-hosting and optimizing LLMs locally, demonstrating curiosity and ability to rapidly adopt emerging AI technologies **❌ Missing Required:** Proven NLP/LLM experience in production environments, TensorFlow or PyTorch at advanced level (only PyTorch mentioned, unclear depth), MLOps practices (CI/CD for ML, model versioning, monitoring), Microservices design and API architecture leadership, Automated testing and code review leadership, B2B product/services integration experience

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate is a highly capable Systems Architect but operates in a completely different technical domain (custom Python, AI/Infra, open-source) from the job's explicit requirements (Microsoft Teams, Microsoft Viva). Despite a matching job title and language skills, there is a critical, insurmountable gap in the core technology stack. **⚠️ Critical Gaps:** - The role requires deep expertise in the Microsoft Teams/Viva ecosystem, whereas the candidate's entire experience is in open-source and custom-built infrastructure (Python, Linux, Docker, AI Clusters). **✅ Strengths:** - Proven Systems Architecture and integration skills - Fluent in Portuguese and based in Brazil - Strong track record of automation and delivering production systems **❌ Missing Required:** Design and development experience in major Viva components, Deep knowledge and experience in Teams Telephony and app development

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5-mini] Strong infra architect with Docker, Terraform, Linux, CI/CD and on‑prem LLM/GPU cluster experience — good transferable skills and fast‑learner potential — but missing core Azure/Azure DevOps credentials and several Azure/Kubernetes monitoring/orchestration skills required by the role. **⚠️ Critical Gaps:** - AZ-400 or AZ-305 (explicitly mandatory certification — blocking) - Azure DevOps (role expects domain ownership of Azure DevOps tooling) - AKS / Kubernetes (role requires solid Kubernetes experience) **✅ Strengths:** - Proven metal-up infrastructure architecture and production system delivery - Hands-on Docker, Terraform, Linux and CI/CD pipelines - Experience deploying and optimizing local AI/LLM GPU clusters (privacy-focused AI ops) **❌ Missing Required:** AZ-400 or AZ-305 certification, Hands-on Azure DevOps (Pipelines/Repos/Artifacts/Boards), AKS / Kubernetes, Azure Key Vault, Monitoring stack (Prometheus/Grafana/Datadog), Harbor (container registry)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a proven systems architect with an impressive ability to self-learn and build complex automated systems from scratch. However, there is a critical and disqualifying gap in the core required technologies: the entire Databricks ecosystem (DBX, Delta Lake, Unity Catalog) and deep AWS-native data services. While they possess strong adjacent skills in Python, SQL, and IaC, they lack the specific, hands-on expertise required to lead the design of a modern data lakehouse on the specified platform. **⚠️ Critical Gaps:** - Databricks / Lakehouse Architecture (no demonstrated experience) - Deep AWS-native data services (resume lists 'AWS Basics' vs. required 'Deep experience') **✅ Strengths:** - Proven ability to architect and build entire automated systems from zero - Strong foundation in Python, SQL, and Infrastructure-as-Code (Terraform) - Demonstrated 'Fast Learner' with a career trajectory moving towards complex technical roles **❌ Missing Required:** End-to-end setup of Databricks workspaces and Unity Catalog, Expertise in Delta Lake internals, Advanced PySpark skills, Deep experience with AWS Glue, S3, Redshift Spectrum, Lambda, and Athena, Strong grasp of modern dimensional modeling (star/snowflake schemas)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture, IaC (Terraform), Python automation and self-hosted AI experience indicate fast learning and a solid cloud foundation, but the resume lacks hands-on Amazon Connect / contact-center and many specific AWS service integrations required for an immediate lead role. **⚠️ Critical Gaps:** - Amazon Connect (platform-specific knowledge) - BLOCKING - Contact center / telephony migration and dialer expertise - BLOCKING - CRM integration with contact center/dialer (operationally critical) - BLOCKING **✅ Strengths:** - Systems architecture and end-to-end automation (metal-up thinking) - IaC and infrastructure automation (Terraform) with Linux/DevOps skills - AI/LLM infrastructure and Python-based automation (fast practical learning) **❌ Missing Required:** Amazon Connect, CloudWatch, API Gateway, AWS Systems Manager, Amazon VPC, Lambda, EC2, ECS, SNS, SQS, Knowledge/experience with Amazon Connect setup and integration, Experience with Pinpoint / Lex integrations

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong architectural and systems thinking with proven ability to bridge business and technology. Candidate demonstrates end-to-end solution design experience, cloud infrastructure knowledge, and data pipeline work. The e-commerce automation system shows capability in building scalable, data-driven solutions. Main gaps are in specific geospatial data experience and retail/martech domain exposure, but the candidate's supply chain background and fast-learner profile (complex systems builder, 33yo with diverse tech stack) suggest strong adaptability. The profile aligns well with the 'bridge' role between business and engineering that HYPR seeks. **✅ Strengths:** - Proven business-technology bridge: Supply chain + finance background transitioning to systems architect mirrors the Solutions Architect role perfectly - End-to-end system ownership: Built production-grade e-commerce automation from concept to deployment with zero manual intervention - Strong architectural thinking: Self-hosted AI infrastructure, automated inventory systems, and algorithmic trading show ability to design complex, integrated solutions **❌ Missing Required:** Geospatial data experience, Retail/media/martech domain experience

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-4.1] The candidate is a highly skilled systems architect and engineer, but lacks both the required degree in Architecture and any experience in Civil Construction projects. None of the core hard skills (project supervision on construction sites, architectural design, reading/conference of blueprints, or site safety/quality in civil works) are present or inferable. The candidate's strengths are in software, automation, and infrastructure, which are not transferable to the strictly required domain of this job. **⚠️ Critical Gaps:** - Formação superior em Arquitetura - Experiência comprovada em projetos de Construção Civil **✅ Strengths:** - Gestão de projetos - Automação e integração de sistemas - Capacidade analítica avançada **❌ Missing Required:** Diploma de Arquitetura, Experiência prática em obras civis

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] The candidate is a highly capable Systems Architect and AI Infrastructure engineer with proven skills in Python, automation, and building complex systems from the ground up. However, there is a fundamental mismatch with the core technology stack required for this role, which is heavily based on Java (JBoss, JPA, EJB) and Frontend (React, Javascript). These represent critical gaps that are too significant to overcome despite the candidate's strong architectural background and learning ability. **⚠️ Critical Gaps:** - Java Enterprise Stack (Java, JBoss, JPA, EJB, etc.) - Frontend Development (Javascript, React) **✅ Strengths:** - Systems Architecture & Design - Python & Automation - Infrastructure as Code (Terraform, Docker) **❌ Missing Required:** Java, JBoss/Tomcat/WildFly, JPA, EJB, Javascript, React, Node.js, C#, Apache Kafka/RabbitMQ, TDD

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: claude-sonnet-4.5] Complete domain mismatch. The job description is for a Physical Architecture position (building/construction architecture) requiring a degree in Architecture ('Ensino Superior em Arquitetura'), driver's license CNH 'B', and 6 months experience in the architectural field. The candidate has a background in Software/Systems Architecture, Mechatronics Engineering, Supply Chain, and AI Infrastructure - completely different from physical building architecture. **⚠️ Critical Gaps:** - Physical/Building Architecture (vs Software Architecture) - Architecture Degree (Arquitetura) - Construction Industry Experience **❌ Missing Required:** Ensino Superior em Arquitetura (Architecture Degree), 6 months experience in architectural function (building/construction), CNH 'B' driver's license

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Complete domain mismatch. The candidate is a Software/Systems Architect specializing in IT, AI, and cloud infrastructure, while the job requires a Civil/Building Architect with a degree in Architecture/Urban Planning and experience with BIM. There is zero overlap in skills or experience. **⚠️ Critical Gaps:** - The candidate's profession is Software/IT Architecture, whereas the job is for Civil/Building Architecture. This is a fundamental and non-transferable domain difference. **✅ Strengths:** - Candidate possesses strong technical skills in an entirely different field (Software Engineering and AI Infrastructure). **❌ Missing Required:** Formação em Arquitetura e Urbanismo, Conhecimento de conceitos BIM e ferramentas, Experiência em projetos de médio e grande porte (em arquitetura civil), Experiência em compatibilização de projetos arquitetônicos

[ANALYSIS_REPORT] **DISQUALIFIED** [Copilot: gpt-5-mini] Candidate demonstrates strong systems architecture, integrations, automation and fast-learning ability but lacks any proven SAP SuccessFactors / SAP HCM / BTP / ABAP experience required for this role, making them unsuitable for immediate delivery on the opening. **⚠️ Critical Gaps:** - Proven experience as an Architect for SAP SuccessFactors (end-to-end) - ABAP HCM / on-prem SAP HCM expertise - SAP BTP + CPI/SCPI integration platform development (CAP/Node/Java) - Experience integrating SuccessFactors with SAP ECC/S4 **✅ Strengths:** - Broad systems architecture and infrastructure experience - Strong automation and engineering delivery using Python - Operability expertise: Docker, Terraform, CI/CD, Linux and security **❌ Missing Required:** Experiência comprovada como Arquiteto SAP SuccessFactors, Conhecimento avançado em SAP HCM e ABAP HCM, Proeficiência em desenvolvimento de extensões no SAP BTP (CAP/Node/Java), Experiência com Integration Center, OData APIs e SAP CPI/SCPI, Responsabilidade por arquitetura end-to-end SuccessFactors + ECC/S4 + BTP

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong analytical, automation, and systems integration skills, with deep experience in data-driven environments and technical system design. They have hands-on experience with ERP, analytics, and reporting, and are fluent in English and Portuguese, but lack explicit experience with CRM, BI/data visualization tools, and advanced Spanish. The candidate's fast-learning profile and broad technical foundation make them a strong fit, with only a few domain-specific gaps. **⚠️ Critical Gaps:** - Advanced Spanish language **✅ Strengths:** - Systems integration and automation - Analytical and data-driven mindset - Experience with ERP and process improvement **❌ Missing Required:** CRM platforms, BI/data visualization tools, Advanced Spanish language

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Pro] The candidate is a strong technical architect with impressive self-taught capabilities and relevant domain experience in finance and consulting. However, the core role is Delivery Management, which is a significant pivot from their hands-on architect background, creating a functional gap. A notable weakness is the lack of deep, required experience in AWS or Azure, with only 'basics' listed. **⚠️ Critical Gaps:** - Formal Delivery Management experience in a corporate setting **✅ Strengths:** - Deep Solution Architecture and systems design experience - Strong client-facing and ownership skills from founder/consultant roles - Proven fast learner with a strategic, business-oriented mindset **❌ Missing Required:** Advanced Cloud Implementation experience (AWS or Azure)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Pro] Candidate possesses strong project management skills but in a completely different domain (technical infrastructure, engineering, finance). There is a critical and fundamental gap in marketing, creator partnerships, and B2B ecosystem knowledge, making them a poor fit despite their proven ability to execute complex projects. **⚠️ Critical Gaps:** - The role requires a marketing project manager, and the candidate's experience is exclusively in technical/engineering and supply chain domains. - Candidate's career trajectory is moving deeper into AI/Infrastructure, which is the opposite direction of this creator/partnerships-focused marketing role. **✅ Strengths:** - Demonstrated end-to-end project ownership from concept to execution - Proven self-starter with entrepreneurial experience - Strong systems and automation mindset **❌ Missing Required:** Experience as a marketing project manager at a brand or agency, Hands-on exposure to formats like podcasts, events, webinars, and sponsorships, Familiarity with creator marketing or brand partnerships, Understanding of the B2B sales and marketing ecosystem, Experience working with creative talent

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Pro] Candidate demonstrates strong, modern aptitude in AI infrastructure and end-to-end systems architecture, aligning with the 'Generative AI' aspect of the role. However, there is a critical, blocking gap concerning the 'Oracle Data Integrator (ODI)' requirement, a specific enterprise ETL platform where the candidate shows no direct or adjacent experience. **⚠️ Critical Gaps:** - Oracle Data Integrator (ODI) - The role is explicitly for a specialist in this platform, and the candidate's experience is in custom Python scripting and open-source tools, a completely different domain. **✅ Strengths:** - Generative AI Infrastructure (self-hosted LLMs) - End-to-End Systems Architecture (from metal to business logic) - Python-based Automation and Logistics **❌ Missing Required:** Oracle Data Integrator (ODI), Asset & Wealth Management domain experience, ODI data modeling and mapping

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-4.1] The candidate demonstrates strong Python, data analysis, and LLM infrastructure experience, with a proven record in building and evaluating AI systems. There is clear evidence of advanced analytics, cloud basics, and end-to-end system integration. The main gap is direct experience with semantic layer tools (Cube Core, dbt, LookML) and hands-on LLM fine-tuning, but the candidate's fast-learning profile and relevant adjacent skills make them a strong fit. **⚠️ Critical Gaps:** - Direct experience with Cube Core or similar semantic layer tools **✅ Strengths:** - Python and automation expertise - LLM infrastructure and privacy-first AI deployments - Complex system architecture and integration **❌ Missing Required:** Hands-on with Cube Core or equivalent semantic layer