Skills
Capabilities across AI/RAG, multi-cloud architecture, platforms, and product-facing solution design, aligned with how I ship in production. Years are approximate hands-on professional use..
AI & Agentic Systems
Approximate years reflect hands-on professional use.
- Production AI beyond chat wrappers (context, evaluation, guardrails)1+ yrs
- Vertex AI, Gemini & Google Cloud AI patterns (when GCP is the fit)1+ yrs
- Azure OpenAI & enterprise LLM integration patterns1+ yrs
- RAG pipelines, hybrid retrieval & agent orchestration1+ yrs
- Model Context Protocol (MCP) & tool-grounded assistants1+ yrs
- AI-assisted & agentic engineering (IDE agents, repeatable workflows)2+ yrs
Cloud Architecture
Approximate years reflect hands-on professional use.
- Provider-agnostic architecture (GCP, Azure, AWS trade-offs & portability)4+ yrs
- GCP: Cloud Run, Pub/Sub, IAM-secure networking patterns3+ yrs
- Azure: Service Bus, core PaaS & hybrid connectivity patterns4+ yrs
- AWS solutions architecture & Well-Architected trade-offs (SA Associate)4+ yrs
- Distributed systems: failure modes, scaling, and operational impact4+ yrs
- Serverless & event-driven integration (Lambda, API Gateway, queues)4+ yrs
Product Architecture
Approximate years reflect hands-on professional use.
- Pre-sales & solution design: options, risks, and decision records1+ yrs
- Cost, scalability, time-to-market & team-maturity aware roadmaps4+ yrs
- Reusable solution frameworks & decision engines for repeatability4+ yrs
- Stakeholder communication: turning fuzzy asks into shippable increments10+ yrs
Platform Engineering
Approximate years reflect hands-on professional use.
- Terraform & infrastructure-as-code (modules, env promotion, drift control)2+ yrs
- GitHub Actions CI/CD & release automation2+ yrs
- Containers & Kubernetes-style ops (ECS/Fargate, Docker)2+ yrs
- Internal developer platforms & golden paths for teams3+ yrs
- Governance in the SDLC: standards, automated checks & quality gates3+ yrs
- Observability baselines (logs, metrics, traces)8+ yrs
Data & RAG
Approximate years reflect hands-on professional use.
- AI-ready data: ingestion, transformation & retrieval at scale1+ yrs
- Embeddings, vector search & structured filters for hybrid retrieval1+ yrs
- Databricks lakehouse (Delta, Jobs, Unity Catalog patterns)1+ yrs
- Lakehouse ETL & platform architecture (AWS + Databricks)1+ yrs
Front-End
Approximate years reflect hands-on professional use.
- TypeScript / JavaScript15+ yrs
- React10+ yrs
- Next.js5+ yrs
- Tailwind CSS & ShadCN-style component systems4+ yrs
- HTML / CSS & responsive layout15+ yrs
- Accessibility & semantic HTML10+ yrs
Back-End
Approximate years reflect hands-on professional use.
- Node.js12+ yrs
- Python (services, automation, data/AI glue)5+ yrs
- C# / .NET14+ yrs
- ASP.NET MVC & web APIs10+ yrs
- REST & GraphQL APIs12+ yrs
- Event-driven & async workflows (queues, webhooks)9+ yrs
- Microservices & domain boundaries8+ yrs
Databases
Approximate years reflect hands-on professional use.
- Microsoft SQL Server12+ yrs
- MySQL2+ yrs
- PostgreSQL4+ yrs
- DynamoDB4+ yrs
- Redis3+ yrs
Agile
Approximate years reflect hands-on professional use.
- Scrum / Kanban14+ yrs
- Technical planning & estimation6+ yrs
- Code review culture6+ yrs
Tools
Approximate years reflect hands-on professional use.
- Git / GitHub4+ yrs
- Docker4+ yrs
- Jenkins & legacy CI integrations2+ yrs