Makro PRO

Role Description This is the contact point for the local team to work closely with the headquarter teams. We are seeking an experienced Senior Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions and who has mind set things to done. - Design, develop, and maintain scalable data pipelines and ETL processes - Implement and optimize data storage solutions, including data warehouses and data lakes - Collaborate with data scientists and analysts to understand data requirements and provide efficient data access - Ensure data quality, consistency, and reliability across all data systems - Develop and maintain data models and schemas - Implement data security and access control measures - Optimize query performance and data retrieval processes - Evaluate and integrate new data technologies and tools - Mentor junior data engineers and provide technical leadership - Collaborate with cross-functional teams to support data-driven decision-making Qualifications - Bachelor's or master's degree in computer science, Engineering, or a related field - 7+ years of experience in data engineering or related roles - Strong programming skills in Python, Java, or Scala - Extensive experience with big data technologies such as Hadoop, Spark, and Hive - Proficiency in SQL and experience with both relational and NoSQL databases - Experience with cloud platforms (AWS, Azure,) and their data services - Knowledge of data modeling, data warehousing, and ETL best practices - Strong problem-solving skills and attention to detail - Excellent communication and collaboration skills Requirements - Experience with stream processing technologies (e.g., Kafka, Flink, or delta live table) - Familiarity with data governance and compliance requirements - Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) - Contributions to open-source projects or relevant certifications - Experience in Tencent big data platform - Experience in PowerBI will be preferable Benefits - 16~20 days of fully-paid annual leaves - Full social insurance and housing fund - Year-end bonus - WLB - No business trip - Best Culture - Clear focus - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

Role Description At CP Axtra, we believe quality is an engineering responsibility. Not something owned by a separate QA team. We are looking for a Senior Software Test Engineer to help build that culture. This role is much more than writing automated tests. You'll work alongside Product Owners and software engineers to ensure quality is considered from feature discovery through production. You'll help teams decide what should be tested, where it should be tested, and how it can be automated efficiently. You'll build tools, frameworks, and engineering practices that enable developers to confidently own quality while continuously improving our software delivery process. Remote candidates outside of Thailand are welcome to apply. Responsibilities - Drive Engineering Quality - Define testing strategies for new features and system capabilities. - Guide engineering teams to apply testing at the right level (unit, integration, contract, end-to-end, performance). - Identify quality risks during design and backlog refinement before implementation begins. - Establish engineering quality standards and continuously improve testing practices across the team. - Build Automation - Design, build, and maintain scalable automation frameworks. - Develop automated tests across API, integration, contract, and UI layers. - Improve CI/CD quality gates to increase deployment confidence. - Continuously improve test reliability, execution speed, and developer feedback loops. - Partner with Product Owners - Collaborate with Product Owners to refine requirements and ensure stories are testable. - Help define clear acceptance criteria and identify edge cases early. - Ensure business workflows can be validated efficiently through automation. - Enable Engineers - Rather than becoming the team's testing bottleneck, you'll help engineers build better software. - Improve Engineering Practices - Recommend improvements to our development workflow, automation strategy, and release process. - Drive adoption of modern quality engineering practices. - Monitor quality metrics and identify opportunities to reduce production defects. - Continuously improve developer experience around testing and automation. - You will also need to: - Coach developers on effective testing practices. - Review designs and pull requests from a quality perspective. - Help teams decide what should—and shouldn't—be covered by automated tests. - Build reusable testing libraries, utilities, and developer tooling. - Promote Shift Left quality practices across the engineering organization. Qualifications - 7+ years of experience in Quality Engineering, Software Engineering, or Test Automation. - Strong software development experience in Java (preferred) or another modern programming language. - Experience building and maintaining automation frameworks rather than simply writing automated tests. - Experience working with distributed systems and microservice architectures. - Strong understanding of: Unit Testing, Integration Testing, API Testing, Contract Testing, End-to-End Testing, Performance Testing principles. - Experience integrating automated testing into CI/CD pipelines. - Experience working closely with Product Owners and software engineers in Agile teams. - Strong analytical and debugging skills. - Excellent written and verbal communication skills. - Expertise in: Java / Spring Boot, REST APIs, SQL, Kafka or event-driven systems, Docker / Kubernetes, GitHub Actions, GitLab CI, Jenkins, or similar, Playwright, Selenium, REST Assured, Pact, JUnit, or similar tools, Datadog, Grafana, or other observability platforms. Nice to Have - Warehouse Management Systems (WMS) - Supply Chain or Logistics systems - Retail technology - Performance testing - Cloud platforms (AWS, Azure, GCP) - Contract testing implementation - Experience coaching engineering teams What Success Looks Like - Within your first year, you'll: - Establish scalable quality engineering practices across our WMS tool. - Improve developer ownership of testing and quality. - Increase automation coverage at the most valuable test layers—not simply increase the number of tests. - Reduce production defects through better engineering practices. - Improve confidence in every deployment through automation and effective quality gates. - Help build a culture where quality is everyone's responsibility. Benefits - Health Insurance – We care about your health! Group insurance from a top insurance company is included in your benefits—OPD, IPD, Emergency OPD. - Provident Fund – We care about your long-term plan! We offer 3% provident fund. - Year-end bonus – We include variable and performance bonus for our employees. - Gym Facilities – Our Head office has a fitness center, yoga room, and recreational space. Enjoy Bangkok scenery and work your body! - Attractive Vacations days – Enjoy our attractive annual leave. Let’s say the minimum is 16 days! - No overtime – We work 5 days a week with. We set our own goals and deadlines. - Cool hardware – New MacBook. The tool to help you be the best of yourself. - Free car parking space – No more stress or extra cost if you drive to work. We offer free parking space for our employees. Company Description - Best Culture - Clear focus. - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

Role Description The Backend Engineer is responsible for the system to work behind the scenes. The role is to integrate the application with all required systems and services and provide clean and easy-to-use API for the frontend part of the system. Although the work is usually hidden from the user, the Backend Engineer bears the full responsibility for the application functionality, performance and scalability. - Design and develop the business logic and backend systems of the product - Work closely with frontend developers to design and develop functional, performing and complete APIs - Decipher existing companies software systems and be able to hook in application to applicable data sources - Write both unit and integration tests, and develop automation tools for daily tasks - Develop high quality, well documented, and efficient code - Challenge ideas and opinions to avoid pitfalls and inefficient solutions Qualifications - You have experience as a backend engineer in common languages and frameworks, e.g., Java, Node Js, ExpressJS, NestJS or any other JS framework - You have experience in AWS - You have experience in GraphQL - You have deep knowledge of object-oriented programming and engineering principles such as SOLID - You have significant experience writing and utilizing autonomous services-oriented restful API services and performance tuning large scale apps - You have experience with database systems, with knowledge of SQL and NoSQL stores, e.g., MySQL, MongoDB, Redis, Postgres - You are able to write effective unit, integration, and API tests. It is a plus if you experience integrating with JavaScript frameworks, such as React Benefits - Full social insurance and housing fund - Year-end bonus - Phone allowance - Transportation allowance - Best Culture - Clear focus. - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

Role Description Senior Manager - Product Owner creates product roadmap and defines the strategic vision for their team driven by the overall vision. They have a deep understanding of the target market/industry and build close relationships with key stakeholders to ensure that the team’s effort is aligned with overall strategy. A Product Owner manages dependencies with other team’s functions while identifying, building and managing strategic partnership across the different teams. They work closely within their team to ensure business value and user feedback is translated into new developments when necessary. Product owners will be accountable for specific business KPIs based on the area of the product they are focused on. - End to end team output strategy from inception to production - Collaboration with stakeholders to ensure the digital vision and e-commerce products align within team strategy and requirements - Accountable for product-specific KPIs once solution enters production and communicate regular tracking to stakeholders - Utilize market and industry knowledge to translate user needs into user stories and acceptance criteria for their team - Maintain a backlog 3 to 4 sprints ahead of the team - Work closely with CPO to establish each product’s business value and support messaging, communication, and customer outreach as necessary - Release planning with stakeholders as well as weekly demos - Integrate usability studies and research into product requirements to enhance user satisfaction and ensure customer driven design - Align outward facing product requirements and stakeholders Qualifications - Ability to develop methods and promote work standards among other employees of the company - Proven skills in managing staff, coaching, resolving conflicts - Strong communication skills to teach and convey messages in a professional form - Ability to create an atmosphere of trust and comfortable/efficient work environment - Belief in a non-hierarchical culture of interaction, openness to new ideas and continuous improvement - Proven knowledge of standard concepts, practices, and procedures within the retail industry - Experience working in the development of B2C e-commerce products - Strong collaborator with cross-functional teams from tech, design, and business - Experience with managing data ingestion, storage, and processing, and collaborate with data professionals to design and implement advanced analytics capabilities Benefits - Health Insurance – Group insurance from a top insurance company is included in your benefits—OPD, IPD, Emergency OPD - Provident Fund – We offer 3% provident fund - Year-end bonus – Variable and performance bonus for our employees - Gym Facilities – Fitness center, yoga room, and recreational space at our Head office - Attractive Vacation days – Minimum of 18 days annual leave - No overtime – We work 5 days a week with self-set goals and deadlines - Cool hardware – New MacBook provided - Free car parking space – No extra cost for employees who drive to work Company Description Makro PRO is an exciting new digital venture by the iconic Makro. Our proud purpose is to build a technology platform that will help make business possible for restaurant owners, hotels, and independent retailers, and open the door for sellers. We welcome bold, energetic, and thoughtful people who share our belief in collaboration, diversity, excellence, and putting customers at the heart of our work. - Clear focus - Diverse Workplace (Our members are from around the world!) - Non-hierarchical and agile environment - Growth opportunity and career path

Role Description The Tech Lead — AI Platform is the senior technical leader for the platform runtime, AI engine, and agent-orchestration tier of an AI-native retail decisioning platform. The role is accountable for architectural integrity, build vs buy decisions, integration with upstream data and knowledge-graph services, and the agent runtime's safety and scale properties — and leads a team of senior software, AI, and ML engineers. Remote candidates outside of Thailand are welcome to apply. - Own the reference architecture for the platform's runtime, decisioning, and agent-execution tiers; co-chair the Architecture Review Board; author Architecture Decision Records. - Design, build, and operate the agent runtime (LangGraph, CrewAI, or chosen framework) — deployment, scale, observability, cost per invocation. - Design and ship an agent autonomy framework with progressive trust levels (shadow / recommender / executor patterns) and measurable gate criteria; operationalise human-in-the-loop patterns for every agent. - Own the agent registry — catalogued, versioned, owned, gated, monitored agents. - Define and operationalise the consumption contract with upstream knowledge-graph, semantic-layer, data-product, and event-stream services from the platform team. - Lead the AI-side decisioning components — orchestrator, trust gate service, agent-side helpers — and coordinate consumption of LLM Gateway and Vector Search services. - Lead a team of senior software, AI, and ML engineers; mentor on agent-engineering discipline; partner with peer Tech Leads on handoffs into application and experience layers. - Own runtime SLOs — invocation P95, success rate, HITL response time — and per-agent cost meter; lead incident response for runtime degradation. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline. - 8+ years software engineering with 3+ years in a Tech Lead / Staff role owning platform standards. - Production agentic systems experience — multi-agent orchestration, HITL gates, eval-driven CI; not just RAG demos. - Strong distributed-systems fundamentals — concurrency, message queues, observability, performance. - LLM platform depth — at least one major provider (Azure OpenAI, Anthropic, Bedrock, Vertex) in production with cost / latency optimisation. - API-first design discipline — service contracts, SLOs, versioning, deprecation policies. - Cloud platform experience (Azure preferred; AWS / GCP transferable). - Architectural authorship — has written ADRs, chaired ARB, made build-vs-buy calls with executive sponsors. Preferred Qualifications - Built or led a production multi-agent platform serving multiple business consumers. - Open-source agent framework contributions (LangChain / LangGraph / AutoGen / DSPy). - Retail / commerce / fintech domain experience; knowledge-graph production experience (Neo4j, Neptune, TigerGraph). - Causal inference exposure (DoWhy / EconML).

Role Description The Tech Lead — Experience & Front-End is the senior front-end leader for an AI-native retail decisioning platform — accountable for multiple distinct user surfaces used by diverse personas across merchandising, supply chain, finance, supplier collaboration, and executive insights. The role owns front-end architecture, design system, accessibility, performance, and multi-surface consistency. Remote candidates outside of Thailand are welcome to apply. Key Responsibilities: - Own the front-end reference architecture — framework choice (React / Next.js or comparable), state management, API layer, design system, observability — and Architecture Decision Records for surface-level decisions. - Co-author and maintain the platform design system and component library; ensure WCAG 2.2 AA accessibility is embedded in every component. - Lead build of the internal agent builder workspace for data-scientist / ML-engineer users — build / eval / deploy agents from a template. - Lead build of the Supplier Portal (web + mobile) for external suppliers — onboarding, purchase order, invoice, trade-deal flows; mobile parity within one release. - Lead build of executive dashboards, workbench surfaces (merchandiser, buyer, planner, finance), the governance console (multi-module: trust gate, cost meter, audit log, AI trust dashboard), and the AI copilot. - Own client-side performance SLOs (LCP, INP, CLS per surface) and instrument client-side observability (errors, performance, usage). - Lead 1–2 senior front-end engineers and 1 UX / Designer; mentor on front-end engineering excellence (performance, accessibility, design-system discipline). - Drive persona usability testing — pre-launch and post-launch per surface. Qualifications - Bachelor's or Master's degree in Computer Science, Design, or a related discipline. - 8+ years front-end engineering with 3+ years in a Tech Lead / Staff role. - Production multi-surface platforms — has led 3+ distinct front-end surfaces. - Strong React / Next.js (or comparable) at staff level; TypeScript at production rigor. - Design system / component library ownership at scale. - Accessibility (WCAG 2.2 AA) — production CI gates, not just lip service. - Mobile experience — at least one production mobile surface (React Native, web mobile, or native). - Performance discipline — LCP / INP / CLS / bundle budgets; cross-team partnership with UX, back-end, product, security. Preferred Qualifications - AI / Copilot surface experience (Cursor, ChatGPT, Claude, GitHub Copilot, comparable). - Builder / low-code-style surface experience (Retool, Toolpad, comparable). - Governance / audit dashboard experience (explainability surfaces). - Open-source contributions to design-system or accessibility tooling.

Role Description The Tech Lead — AI Applications is the senior technical leader for the product-suite implementation tier of an AI-native retail decisioning platform — the commercial layer that delivers measurable business outcomes through a portfolio of product suites and agents. The role is accountable for suite-service implementation, agent integration into business workflows, bounded-context discipline, and partnership with suite product owners. Remote candidates outside of Thailand are welcome to apply. - Own the application-tier reference implementation patterns — service template, bounded-context layout, anti-corruption-layer pattern, contract-test framework, eval harness. - Lead the first commercial suite implementation (supplier collaboration) — services, bounded contexts, end-to-end agent-driven workflows for supplier onboarding, trade deals, invoice reconciliation, and contract intelligence. - Enforce domain-driven-design discipline — bounded contexts own their data; legacy integration via anti-corruption-layer only; never direct database writes to systems of record (Oracle, SAP, WMS). - Co-chair the agent review forum — new agent approvals, eval results, retire decisions; drive per-agent eval harness (golden sets, regression gates, multi-step replay). - Partner with peer Tech Leads on tier-handoff contracts — agent invocation, human-in-the-loop gate handoff, output handling, surface integration. - Be the senior engineering peer for all suite Product Owners; translate suite roadmap into engineering plans (sequencing, dependencies, gates). - Lead senior software engineers on suite-side work; mentor on domain-driven design, bounded-context discipline, and anti-corruption-layer patterns. - Track per-suite commercial KPIs (rebate uplift, forecasting parity, markdown / promo / assortment uplifts) and report to programme leadership monthly. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline. - 8+ years software engineering with 3+ years in a Tech Lead / Staff role with multi-team delivery. - Production retail / commerce / fintech experience — POS, replenishment, merchandising, supplier portal, finance reconciliation. - Domain-driven-design discipline — bounded contexts, aggregates, events, anti-corruption layers — at production scale. - Strong service-oriented architecture; Python or TypeScript at staff level; event-driven systems. - ACL pattern experience — has integrated legacy systems of record (Oracle, SAP, WMS) without leaking into new bounded contexts. - Agent or LLM service consumption in production from a business-domain service. - Cloud platform experience (Azure preferred; AWS / GCP transferable). Preferred Qualifications - Retail technology background — POS, replenishment, supplier collaboration, merchandising, finance reconciliation. - DDD community contributions (talks, papers, open source); strangler-fig legacy-migration experience. - Multi-suite product delivery — has shipped 3+ product surfaces in parallel. - Production event-driven systems (Kafka, Event Hubs) and contract testing at scale.

Role Description The ML Engineer builds the classical retail-ML cores that power the highest-stakes agents on an AI-native retail decisioning platform — demand forecasting that must beat a legacy system, replenishment and allocation models, causal-insight models for executive narratives, and pricing / promotion / markdown / assortment models. The role consumes the enterprise MLOps platform (model registry, drift detection, feature store, library wrappers) and contributes use-case-specific implementations. Remote candidates outside of Thailand are welcome to apply. Key Responsibilities - Build, train, evaluate, and deploy classical retail ML models — forecasting, replenishment, allocation, causal inference (DoWhy / EconML), pricing elasticity, promotion lift, markdown optimisation, assortment. - Use company-curated classical ML wrappers (Prophet, statsmodels, DoWhy / EconML, LightFM, scikit-learn, XGBoost, LightGBM) — do not rebuild open-source libraries from scratch. - Author per-model evaluation methodology appropriate to each model class (forecast MAPE, classification accuracy / precision / recall, causal precision). - Register every model in the enterprise Model Registry with model cards; configure drift-detection thresholds; use the enterprise Feature Store for shared features. - Beat a legacy forecasting system by a measurable margin (MAPE improvement) and document evidence for trust-gate progression alongside the legacy run. - Build causal models for executive-insight agents using DoWhy or EconML; document causal assumptions; ensure mandatory citations for narrative outputs. - Partner with AI Engineers on ML model ↔ agent integration (invocation contracts, latency budgets, fallback behaviour); co-design HITL gate criteria for ML-heavy agents. - Partner with Suite Product Owners on BU adoption, gate criteria, success metrics; document per-model business value (forecast accuracy → inventory savings, replen accuracy → stock-out reduction). Qualifications - Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or a related discipline. - 5+ years building production ML systems with retail or commercial decisioning models (forecasting, replenishment, pricing, recommendation, or comparable). - Strong Python and Spark / PySpark; SQL fluency. - MLOps consumer experience — has registered models, configured drift, used a feature store. - Cloud + Databricks (or equivalent lakehouse) production experience; Azure preferred. - Causal inference exposure (DoWhy / EconML). - Eval discipline — knows how to design appropriate evals per model class. - Retail / commerce domain fluency or rapid acquisition. Preferred Qualifications - Retail forecasting at multi-store / multi-SKU scale; promotional lift / markdown optimisation in production. - Causal inference in commercial decisioning; replenishment / allocation algorithms. - Online learning / near-real-time inference. - Vendor certifications such as Databricks Machine Learning Professional or Azure AI Engineer Associate.

Role Description The Head of Retail AI Platform is the senior leader accountable for an AI-native retail decisioning platform end-to-end — strategy, roadmap, delivery, team, governance, and commercial outcome. The platform delivers a portfolio of product suites and agents to merchandising, supply chain, finance, supplier collaboration, and executive-insight users, operating a multi-million-baht programme with a senior engineering team. Remote candidates outside of Thailand are welcome to apply. - Own the platform roadmap end-to-end — phased multi-release delivery, suite sequencing, agent prioritisation, budget vs scope; resolve open strategic and architectural decisions on documented timelines. - Run the platform operating model — Steering Committee, Architecture Review Board, AI governance reviews, cost review, data-product contracts review — with executive sponsors and peer technology directors. - Lead phased multi-release delivery across an 18–24-month horizon — foundation launch, supplier-collaboration suite, retail-operations and executive-insights suites, then commerce-intelligence suite — each with measurable commercial outcomes. - Lead recruitment of the engineering leadership team and the broader IC team; set engineering culture (domain-driven design, agent-native, retail-specific, human-in-the-loop by default). - Own the peer-platform interface — data platform / engineering / governance — operationalise the service contracts (LLM gateway, knowledge graph, data products) and resolve scope-overlap escalations. - Chair governance for agent autonomy progression (shadow / recommender / executor patterns) with measurable criteria and stakeholder sign-off. - Own the commercial narrative with executive sponsors — quarterly business review, ROI tracking, budget burn, run-cost trajectory; defend the platform to the CFO office. - Manage risk — capital exposure on build vs buy, vendor lock-in, regulatory exposure, delivery slippage — with a documented register and clear mitigations. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Business, or a related discipline. - 12+ years in software / data / AI engineering with 5+ years in a senior leadership role (Director / Head / VP) accountable for product delivery and team P&L. - Shipped AI-native products at scale — agentic systems, ML platforms, decisioning engines, or comparable — with demonstrable commercial outcomes, not just demos. - Strong technical depth in at least one of: agent runtimes (LangGraph, CrewAI, AutoGen), LLM platforms, classical ML deployment at scale, lakehouse architectures, knowledge graphs. - Programme governance experience — chairing steering committees, presenting to executive sponsors, managing capital budgets at the tens-of-millions scale. - Built and retained engineering teams at 20+ FTE scale in Southeast Asia. - Cross-functional partnership — has navigated peer-platform organisations, Legal / DPO, InfoSec, CFO office. - Excellent written and verbal communication; speaks finance, technology, and business with equal credibility. Preferred Qualifications - Retail technology background — POS, replenishment, merchandising, loyalty, supply chain. - Regulated-AI experience (banking, healthcare, public sector); multi-cloud or hybrid production environments. - Open-source platform leadership; public speaking / thought leadership in AI or agentic systems. - Executive education in AI strategy or digital transformation (MIT Sloan, INSEAD, Stanford or comparable).

Role Description The DevOps / SRE Engineer owns the operational substrate of an AI-native retail decisioning platform — infrastructure, CI / CD, observability, cost meter, and incident response for a system that runs production agents taking real business actions. The role builds on the enterprise Terraform standard, CI / CD spine, and FinOps tagging policy rather than reinventing parallel infrastructure. Remote candidates outside of Thailand are welcome to apply. - Adopt the enterprise Terraform standard and module library for all platform infrastructure; author platform-specific modules where needed (agent runtime, vector DB, knowledge graph); run drift detection weekly. - Build platform-specific CI / CD pipelines on the enterprise spine — service deploys, agent deploys, eval-gate enforcement; integrate eval gates so no agent reaches production without eval pass. - Operate rollback orchestration with sub-15-minute recovery; quarterly game days. - Own the platform observability stack — OpenTelemetry, Langfuse for LLM traces, custom dashboards for per-agent cost. - Implement the per-agent cost meter end-to-end — token counts, vector queries, model inference, downstream LLM Gateway costs; surface cost data to the enterprise GenAI cost dashboard. - Stand up the platform on-call rotation; author runbooks for every production agent and service; lead incident response with measurable corrective actions. - Implement platform cost-tagging policy consistent with the enterprise standard (team, domain, environment, project, agent, suite, persona); report monthly to Cost Review. - Drive cost optimisation — right-sizing, caching, model routing decisions, reserved compute. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline. - 5+ years SRE / DevOps with production ownership. - Terraform at scale — modules, state, drift, environment promotion. - CI / CD for data + ML / AI services (GitLab CI / CD or comparable). - Cloud platform (Azure preferred; AWS / GCP transferable). - Observability — OpenTelemetry, Langfuse (or comparable LLM traces), custom dashboards. - FinOps — tagging policies, attribution, optimisation. - Incident response — on-call, post-mortems, runbook authorship. Preferred Qualifications - AI / agent platform SRE experience; cost-meter / chargeback systems built or operated. - Multi-cloud production experience; open-source contributions to IaC / observability tooling. - AI / ML / agent system observability instrumentation (LLM cost, agent cost, eval scores). - Vendor certifications such as HashiCorp Terraform Associate / Professional, Azure Solutions Architect Associate, or Databricks Data Engineer Professional.