Anti-ATS Evaluatorv1.3

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4] Strong technical foundation with AI/ML experience and systems architecture background. Candidate demonstrates hands-on AI deployment (self-hosted LLMs) and automation expertise. Missing formal pre-sales experience and specific Microsoft Azure/Fabric knowledge, but shows strong learning capability and relevant technical depth. **✅ Strengths:** - AI/ML hands-on experience with LLMs - Python expertise with ML libraries - Systems architecture and automation **❌ Missing Required:** 5+ years pre-sales/solution consulting experience, Microsoft Fabric familiarity, Azure ecosystem knowledge

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5.1] O candidato tem forte background em arquitetura de sistemas, automação e integrações via APIs, mas carece de experiência explícita com plataformas de integração corporativa (ESB/API Gateway) e padrões clássicos de integração (SOAP, mensageria, microsserviços), que são centrais para a vaga. A base técnica, exposição a nuvem, CI/CD e segurança indicam alto potencial de aprendizado rápido e boa capacidade de transição para o papel de Arquiteto de Integração. **⚠️ Critical Gaps:** - Hands-on com plataformas de integração/ESB (MuleSoft, Dell Boomi, Azure Integration Services ou similares) - Desenho de arquiteturas de integração baseadas em mensageria e microsserviços - Experiência prática com integrações SOAP e protocolos legados em ambiente corporativo **✅ Strengths:** - Histórico sólido de projetar e operar sistemas integrados de ponta a ponta com alta automação (Python, scripts, APIs). - Experiência com infraestrutura, Docker, CI/CD e nuvem, dando boa base para integrações escaláveis e ambientes híbridos. - Forte visão de negócio em Supply Chain e Finanças, aliada a segurança (SSO, RBAC) e proficiência em inglês, alinhada ao papel de arquiteto. **❌ Missing Required:** Experiência comprovada e explícita em arquitetura de integração corporativa, Desenvolvimento e publicação de APIs próprias (não apenas consumo) em escala empresarial, Padrões de integração SOAP, Padrões de mensageria (fila, publish/subscribe) com ferramentas de mercado, Arquitetura de microsserviços focada em integração entre sistemas, Ferramentas de integração dedicadas (MuleSoft, Dell Boomi, Azure Integration Services, ESB/API Gateway similares)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents as a highly skilled Solution Architect with strong technical acumen, proven experience (6+ years), and a clear career trajectory towards complex systems. They excel in general architecture, analytical problem-solving, and cloud fundamentals. However, the candidate has significant gaps in the specific domains required by the job, notably regulatory compliance (LGPD, audits, reporting) within the energy sector, and direct experience with CRM/omnichannel, billing, and collection platforms. While the candidate is a fast learner, these are critical functional domain gaps that cannot be easily inferred. **⚠️ Critical Gaps:** - LGPD/Regulatory compliance expertise (especially within energy and billing/collection contexts) **✅ Strengths:** - Extensive Solution Architecture experience (6+ years) with a focus on 'metal-up' and self-sustaining systems. - Proven ability to design and implement complex, automated systems (JIT inventory, AI clusters, trading bots), demonstrating strong analytical and problem-solving skills. - Strong technical foundation in Cloud (AWS in progress, Docker, Terraform), Python, SQL, and general infrastructure, coupled with a 'Fast Learner' aptitude for new technologies. **❌ Missing Required:** Knowledge of Energy market, Knowledge in Agile methodology, tools JIRA and Confluence, Experience with CRM/omnichannel integrations, service platforms, billing/cobrança and regulatory compliance

[ANALYSIS_REPORT] **WEAK_MATCH** [G2.5 Flash] The candidate demonstrates exceptional technical depth in ML/AI infrastructure, systems architecture, and data-driven business transformation, supported by a strong self-learner trajectory. However, the role's emphasis on direct pre-sales, technical account management for very large enterprise clients, and explicit experience with the Databricks/Spark ecosystem represents a significant gap, leading to a weaker overall match for this specific Solutions Architect position. **⚠️ Critical Gaps:** - Direct pre-sales experience and track record with very large (>$1m ARR) global enterprise accounts, especially in a platform sales motion. **✅ Strengths:** - Deep expertise in ML/AI infrastructure and application development. - Strong systems architecture and technical implementation skills with a focus on business impact. - Proven ability in data-driven business transformation and a track record as a fast learner. **❌ Missing Required:** Explicit pre-sales professional experience for a data platform, Demonstrated experience working with very large (>$1m ARR) global accounts (from a client-facing/pre-sales perspective), Direct expertise in Big Data platforms relevant to Databricks (e.g., Apache Spark)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates exceptional expertise in systems architecture, backend development (API-first), cloud-native infrastructure, and automation, with direct experience relevant to e-commerce and large-scale systems. While possessing strong architectural foundations and a proven ability to deliver production-grade solutions, a critical gap exists in explicit frontend development experience, particularly with React, which is a stated core requirement for this fullstack role. This makes it a challenging match for a true 'Fullstack Solution Architect' position. **⚠️ Critical Gaps:** - Frontend Development (React) **✅ Strengths:** - Robust Systems Architecture and Integrator experience, with proven ability to build complex, production-grade backend systems (JIT inventory, AI clusters). - Deep expertise in cloud-native technologies (Docker, Terraform, AWS Basics, CI/CD, Linux) and relational databases/advanced SQL. - Intentional career progression towards technical/architectural roles with significant self-teaching and 'Fast Learner' bonus, demonstrating adaptability and drive. **❌ Missing Required:** Modern CMS solutions (headless and traditional), Headless architecture, Specific web frameworks (beyond general API backend), Event-driven design

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong infra and backend systems experience (Docker, Terraform, CI/CD pipelines, AWS basics, production automation) and clear fast-learning evidence (self-hosted LLMs, end-to-end production systems). Major gaps are the primary development stack (Node.js/TypeScript/NestJS) plus frontend (React) and Kubernetes which are central to the role, so candidate is promising but needs upskilling on those core items. **⚠️ Critical Gaps:** - Node.js/TypeScript (primary backend language stack) - NestJS (framework explicitly required) - React (frontend requirement) - Kubernetes (orchestration required for production) **✅ Strengths:** - Infrastructure-as-code and automation (Terraform, pipelines, Docker) - Proven end-to-end system design and production deployment (JIT system, API integrations) - Fast learner with hands-on experience in emergent AI infra and complex ops **❌ Missing Required:** Node.js, TypeScript, NestJS, React, Kubernetes

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: gpt-5.1] Strong background in systems architecture, automation, and supply chain/finance data flows maps well to integration work, but lack of explicit SAP interface experience and advanced Spanish creates meaningful risk for a SAP-centered, bilingual integrations architect role. **⚠️ Critical Gaps:** - Explicit SAP ERP experience (R/3, S/4HANA, or Business One) in integration/interface roles - Advanced professional proficiency in Spanish for stakeholder and vendor communication - Direct experience leading large-scale SAP or multi-ERP interface programs in enterprise environments **✅ Strengths:** - End-to-end systems architecture and automation across multiple business domains (supply chain, trading, operations) - Strong Python, data, and analytics background well-suited for complex interface and data-flow analysis - Proven techno-functional bridge between business stakeholders and technical implementations, aligned with the architect-consultant nature of the role **❌ Missing Required:** Experience working with SAP R/3, SAP S/4HANA, or SAP Business One, Strong hands-on experience integrating SAP with non-SAP systems in production, Advanced professional proficiency in Spanish

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5-mini] Strong systems-architecture, Python, infra-as-code and AI/LLM experience suggest quick ramp-up potential, but the role requires deep, hands-on Amazon Connect/Contact-Center and CRM integration expertise that are not present on the resume. **⚠️ Critical Gaps:** - Amazon Connect (deep, production experience) - CRM integrations with Salesforce or ServiceNow - Amazon Q for Connect / Contact Lens (real-time contact-center AI) **✅ Strengths:** - Systems architecture & building end-to-end automated production systems - Python development and LLM/AI deployment experience - Infrastructure skills: Terraform, Docker, Linux, CI/CD and Git workflows **❌ Missing Required:** Proven Amazon Connect expertise (voice/chat flows, Contact Lens), Advanced proficiency with Amazon Q for Connect, Hands-on CRM integrations (Salesforce, ServiceNow), Practical AWS Lambda serverless implementations tied to contact center

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong technical background in AI/ML solution design, infrastructure, and has a proven track record of hands-on delivery. However, there's a significant gap in explicit pre-sales/RFP leadership experience and slightly less overall IT industry experience than required, which impacts the final score. The candidate's strong learning ability and relevant career progression are significant assets. **✅ Strengths:** - Strong AI/ML Solution Design & Implementation (LLMs, traditional ML, Python) - Proven ability to architect and build complex systems (JIT, AI clusters) - Exceptional self-taught capabilities and relevant career trajectory towards AI **❌ Missing Required:** 5+ Years of experience in pre-sales, solution consulting, or technical account manager role with proven track record of leading technical responses to RFPs and RFIs, 8+ Years of experience working in the IT industry

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: gpt-5.1] Strong hands-on architecture, automation, and analytics background with clear ability to build from scratch, but limited explicit experience in formal data practice building, data governance/quality frameworks, and modern cloud data platforms commonly expected for this role. **⚠️ Critical Gaps:** - Proven experience building or scaling a data practice or data consulting capability - Previous experience working for a mid-size or global consulting organization focused on data - Explicit leadership of data governance and data quality initiatives - Deep hands-on experience with modern cloud data platforms used as shared enterprise data foundations **✅ Strengths:** - Hands-on systems and solution architecture experience building complex, automated data-driven systems from scratch - Strong Python, SQL, and quantitative background relevant to data engineering and analytics foundations - Proven ability to operate independently in ambiguous environments and design self-sustaining, ROI-focused platforms **❌ Missing Required:** Previous experience working for a consulting organization (mid-size or global) focused on data or digital transformation, Proven experience building or scaling a data practice, service offering, or consulting capability, 10+ years explicitly leading or delivering data engineering, data architecture, analytics, or data governance initiatives, Documented design and implementation of data governance frameworks, Documented design and implementation of data quality and reliability frameworks

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate presents a very strong profile with over 10 years of experience in solutions architecture, DevOps, and Python automation. Their proven ability to architect and deploy complex, self-sustaining systems, combined with a fast-learning track record and clear career progression towards technical and AI roles, makes them an excellent fit. While lacking explicit deep experience with specific cloud-native data platforms like Snowflake and Azure, the candidate's strong foundational cloud and infrastructure skills suggest a high potential for rapid upskilling. **✅ Strengths:** - Cloud Infrastructure & DevOps (Terraform, CI/CD, Docker, Linux, Git) - Solutions Architecture & System Design (JIT, AI clusters, production systems) - Automation & Python Proficiency (scripting, bots, operational efficiency) **❌ Missing Required:** Deep knowledge of Snowflake, Deep knowledge of Redshift, Deep knowledge of Azure Data Warehouse, Deep knowledge of Azure ecosystem (S3, ADLS, Kinesis, Data Factory, DBT, Kafka), Deep knowledge of AWS ecosystem (S3, Kinesis, Data Factory, DBT, Kafka) - beyond 'basics', Expertise with Fivetran, Expertise with Spark, Expertise with Matillion, Expertise with AWS Data Migration Services, Expertise with Azure Data Factory

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate, despite demonstrating strong general systems architecture and technical leadership capabilities, entirely lacks the specialized SAP SuccessFactors and SAP BTP experience explicitly required for this role. This fundamental domain mismatch leads to multiple critical skill gaps, making the candidate unsuitable for the position. **⚠️ Critical Gaps:** - SAP SuccessFactors Architect experience - SAP HCM - SAP SuccessFactors - ABAP HCM - SAP BTP / SCPI - Experience with BTP extensions (CAP, Node.js and/or Java) **✅ Strengths:** - Strong Systemic Vision & Technical Leadership - Proven track record in building complex, production-grade automated systems - Fast Learner with continuous education and self-taught expertise in new domains

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong systems architecture and automation skills with Docker, CI/CD, and a notable fast-learner trajectory. However, there's a significant gap in proven, broad Cloud Architect experience, specifically strong knowledge of Azure and enterprise-level AWS, and hands-on Kubernetes expertise as required by the role. **⚠️ Critical Gaps:** - Experiência comprovada como Arquiteto Cloud e gerenciamento de soluções Cloud **✅ Strengths:** - Strong systems architecture and automation capabilities (Python, JIT systems). - Proficiency with Docker and experience in CI/CD pipelines. - Proven fast learner and self-starter with clear technical career progression. **❌ Missing Required:** Azure (Forte Conhecimento), AWS (Forte Conhecimento - além do básico), Kubernetes (incluindo AKS Microsoft)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate is a strong Solution Architect with deep experience in AI, Cloud, Data, and Security, complemented by proven system design and automation. They demonstrate strong leadership and communication skills for complex technical environments. However, there are notable gaps in mainframe platform knowledge and specific enterprise architecture frameworks like TOGAF/IAF. **⚠️ Critical Gaps:** - Mainframe platform **✅ Strengths:** - AI Infrastructure & Cloud Architecture Expertise: Demonstrated through self-hosted LLM clusters, AWS basics, Docker, Terraform, and a clear career trajectory towards AI. - End-to-End System Design & Automation: Proven by architecting JIT inventory systems, production-grade systems, and custom automation pipelines using Python and APIs. - Strong Leadership & Communication in Complex Technical Environments: Evidenced by 'Head of Engineering' role, strategic vision, and C2 English proficiency, making them an effective 'Technical Bridge'. **❌ Missing Required:** Mainframe platform, TOGAF, IAF

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate is a very strong match, possessing significant experience in e-commerce, solution architecture, and leadership, directly aligning with core job requirements. While some specific JS frameworks and methodologies are not explicitly listed, the candidate's 'Fast Learner' trait and demonstrated ability to build complex systems with core modern technologies like Python, AWS, SQL, CI/CD, and AI/ML bridge most gaps, indicating high adaptability and capability for the role. **✅ Strengths:** - Strong E-commerce/Marketplace experience with demonstrated impact (JIT system). - Proven leadership and management skills in highly technical environments. - Exceptional 'Fast Learner' ability with direct relevance to innovative tech (AI/ML, Cloud). **❌ Missing Required:** JavaScript frameworks (Angular, React, Node), Middleware, mobile, and content management experience, Multiple methodologies (Agile/Scrum, Waterfall, etc.), 15 years of experience in solution architecture (candidate has ~12 years)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong background in system architecture, automation, and Python-based data processing, demonstrating a rapid learning ability and a clear career progression towards technical and AI roles. However, a significant gap exists in the required mastery of specific AWS data services, which is critical for the role. **⚠️ Critical Gaps:** - Domínio de serviços AWS (S3, Glue, Redshift, Lake Formation, Athena) **✅ Strengths:** - Proven ability to architect and implement complex, production-grade automated systems, particularly with Python. - Strong demonstrated capacity for rapid self-learning and intentional career growth in advanced technical and AI domains. - Extensive experience in developing and managing data flows, automation scripts, and CI/CD pipelines. **❌ Missing Required:** Experiência em engenharia de dados (streaming pipelines), Vivência em transformação de dados (PySpark)

[ANALYSIS_REPORT] **WEAK_MATCH** [Copilot: claude-sonnet-4.5] Candidate demonstrates strong systems thinking and architectural abilities with 10+ years experience building production systems. However, this role requires deep Databricks expertise and enterprise data platform experience that are not present in the resume. The candidate has foundational Python/SQL skills and AWS basics, but lacks the 8+ years data engineering specialization and hands-on Databricks experience that are hard requirements. The 'AWS Basics' notation suggests surface-level cloud knowledge vs. the deep AWS architecture expertise needed. **⚠️ Critical Gaps:** - No Databricks experience (primary technology requirement) - Lacks 8+ years data engineering/architecture specialization (has ~10 years but in different domains) - No demonstrated experience with enterprise-grade data platforms - Limited AWS depth (resume states 'AWS Basics' vs. required deep expertise) **✅ Strengths:** - Strong systems architecture mindset with proven track record building production systems from scratch - Excellent bridge between business and technical domains (Supply Chain/Finance + Engineering) - Demonstrated 'fast learner' profile with self-directed AI infrastructure and automation projects **❌ Missing Required:** Databricks production experience, PySpark hands-on expertise, Enterprise data platform design, Deep AWS architecture knowledge, Distributed data systems experience, 8+ years in data engineering/solution architecture domain

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a strong background in practical systems architecture, AI infrastructure, and complex system design, aligning well with the role's core responsibilities. While demonstrating an impressive fast-learner aptitude and relevant experience, there's a critical gap in explicit advanced proficiency with formal Enterprise Architecture Frameworks and a slight shortfall in the required 12 years of experience. **⚠️ Critical Gaps:** - Advanced proficiency in Enterprise Architecture Framework **✅ Strengths:** - Extensive practical experience in designing and delivering complex, automated systems and AI infrastructure. - Strong 'Fast Learner' profile with a demonstrated ability to acquire and apply new technical domains rapidly. - Proven ability to bridge business goals with technical architecture and collaborate across teams. **❌ Missing Required:** Advanced proficiency in Enterprise Architecture Planning

[ANALYSIS_REPORT] **STRONG_MATCH** [G2.5 Flash] The candidate is a very strong match for the Solution Architect role, demonstrating extensive experience in system design, infrastructure, and automation, directly aligning with most core requirements. Key strengths include practical API integration, CI/CD, security expertise, and a proven track record of architectural leadership and trade-off analysis. The primary areas for improvement are the explicit mention of Kubernetes and specific Web Portal modernization experience, though these are largely mitigated by inferable skills. **✅ Strengths:** - Solid Solution Architecture and System Design Experience (10+ years, including founder role) - Strong hands-on technical skills in Infrastructure, Automation (Docker, CI/CD, Python, APIs, Linux, Security) - Demonstrated ability in Technical/Business Trade-off Analysis and delivering ROI-focused, resilient systems **❌ Missing Required:** Experiência em modernização/migração de portais Web

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a very strong profile for an Infrastructure Architect role focused on SRE, Observability, and Always On principles, demonstrated through hands-on experience building resilient and automated production systems, including self-hosted AI clusters. The primary gap is the lack of explicit ServiceNow experience, a specific required tool. **✅ Strengths:** - CI/CD Pipelines Expertise - High Availability & Operational Resilience Architectures - Robust Automation and Systems Integration **❌ Missing Required:** ServiceNow experience

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents extensive experience in operational and integration architecture, demonstrated by architecting and implementing complex systems like an automated JIT inventory and self-hosted AI clusters. While a strong technical background, fast learner, and relevant domain expertise are clear strengths, a specific gap exists in the advanced proficiency of enterprise architecture frameworks (e.g., TOGAF) explicitly required by the role. **✅ Strengths:** - Extensive experience in Operational and Integration Architecture, demonstrated by building complex, automated systems. - Proven ability to design, implement, and operate production-grade solutions with strong business impact (e.g., JIT inventory, LLM clusters). - Strong foundation in core infrastructure technologies (Docker, Terraform, Linux, Git/GitHub) and a track record of continuous learning and technical progression. **❌ Missing Required:** Proficiência avançada em Arquitetura de Frameworks (TOGAF, Zachman, ArchiMate ou similares)

[ANALYSIS_REPORT] **GOOD_MATCH** [G2.5 Flash] The candidate presents a compelling profile with extensive solution architecture and data engineering experience, particularly strong in Python, SQL, and building complex, automated systems. While their 'Fast Learner' trait and career progression are significant strengths, the explicit requirements for deep, hands-on expertise in Databricks, PySpark, and AWS are critical gaps that reduce the overall match quality. **⚠️ Critical Gaps:** - Databricks (production and architectural experience) **✅ Strengths:** - Proven Solution Architecture and Systems Integration experience with a strong track record of building automated, production-grade systems. - Deep expertise in Python and SQL, applied at scale in various data-intensive projects. - Demonstrated 'Fast Learner' ability and a clear, progressive career trajectory towards technical and AI infrastructure. **❌ Missing Required:** Deep, hands-on AWS expertise, PySpark

[ANALYSIS_REPORT] **DISQUALIFIED** [G2.5 Flash] The candidate possesses robust technical architecture and system implementation skills, demonstrating a strong aptitude for self-learning and building complex, automated solutions from the ground up. However, the role is explicitly within the 'Global Sustainability Practice' and requires extensive experience and deep understanding of the sustainability industry, which are entirely absent from the candidate's resume, creating a critical domain mismatch. **⚠️ Critical Gaps:** - 5+ years of experience in the sustainability industry - Deep understanding of sustainability industry trends, challenges, opportunities **✅ Strengths:** - Strong technical architecture and system implementation skills (e.g., JIT inventory, LLM clusters, trading bots) - Proven ability to self-teach and master complex technical domains (e.g., AI infrastructure, algorithmic trading) - Extensive experience in full lifecycle system design, automation, and operational excellence across various industries **❌ Missing Required:** Ability to listen and understand prospect/customer sustainability “pain points”, and address those pains by mapping to Schneider Electric strategy, technology, and consulting solutions (specifically within the sustainability context)

[ANALYSIS_REPORT] **POOR_FIT** [G2.5 Flash] The candidate demonstrates strong general architecture, leadership, and system integration capabilities, alongside a clear track record as a fast learner. However, the core requirements of the role are deeply rooted in the SAP SuccessFactors ecosystem, an area where the candidate shows no explicit or inferable experience, creating a significant and blocking domain mismatch. **⚠️ Critical Gaps:** - Required skill in completely different domain: SAP SuccessFactors ecosystem **✅ Strengths:** - Strong architecture and system integration experience - Proven technical leadership and communication skills - Exceptional fast-learner with diverse technical domain exposure **❌ Missing Required:** Experiência comprovada como Arquiteto SAP SuccessFactors, Conhecimento avançado em SAP HCM, Conhecimento avançado em SAP SuccessFactors, Conhecimento avançado em ABAP HCM, Conhecimento avançado em BTP/CPI, Experiência com Integration Center, Experiência com APIs OData (SAP context), Experiência com SCPI, Desenvolvimento de extensões no SAP BTP (CAP – Node/Java)

[ANALYSIS_REPORT] **GOOD_MATCH** [Copilot: claude-sonnet-4.5] Strong technical foundation with systems architecture experience and cloud basics. Candidate demonstrates hands-on infrastructure work (Docker, Terraform, CI/CD) and has built production systems from scratch. However, lacks enterprise-level cloud platform depth (Azure/AWS/GCP PaaS services), messaging systems (Kafka/RabbitMQ), and formal architecture documentation tools (UML, C4, ArchiMate). The 3x/week on-site requirement in São Paulo may be a logistical challenge. Fast learner with proven ability to master complex technologies independently (self-hosted LLMs, automated JIT systems). Age and system-building experience suggest strong adaptation potential. **✅ Strengths:** - End-to-end system architecture: Built production-grade automated e-commerce platform achieving 95%+ inventory accuracy with zero manual intervention - Infrastructure as Code & DevOps: Hands-on Terraform, Docker, CI/CD pipelines, Git/GitHub - solid foundation for cloud-native development - Security awareness: Demonstrated SSO (OIDC/SAML), RBAC, AI privacy concerns - understands modern security practices **❌ Missing Required:** Enterprise cloud platform depth (Azure/AWS/GCP PaaS), Message broker experience (Kafka or RabbitMQ), GraphQL implementation, Formal architecture documentation (UML/C4/ArchiMate)