Bogdan Alex P.

One engineer. Whole product. I build AI systems that ship — RAG pipelines, LLM agents and chatbots on OpenAI, Anthropic Claude and AWS Bedrock — plus full-stack SaaS in Next.js, Python and NestJS. From the AI strategy call to the running system in production. I'm a senior full-stack engineer with a decade of shipping behind me, and over the last few years, AI integration has become the part of the work I'm most useful at. Not as a prompt engineer or a deck-and-disappear consultant, but as the person who sits in a discovery call, understands your product and workflows, identifies where a model, an embedding store or an agent actually moves the needle, and then builds it. Same pair of hands, all the way through. That's the part most teams are missing right now. AI consultants who can't ship. Engineers who can ship but can't tell you whether the LLM is the right answer in the first place. I do both, and the value is in not splitting them apart. How engagements usually start Most projects start with a call. You tell me what you're trying to build or where you're stuck, I ask questions, and we figure out together whether AI is actually the right answer, and if so, what the smallest useful first step looks like. Sometimes that's a one-page plan and an estimate. Sometimes it's a longer paid discovery if the product is complex enough to warrant it. Either way, I'll tell you honestly when an LLM is the wrong answer. That's part of the value of talking to someone who builds these systems, not just advises on them. What I build – AI & LLM integration · OpenAI, Anthropic Claude, Vertex AI, AWS Bedrock, LangChain, LangGraph. RAG systems, chatbots, agentic workflows, prompt and eval pipelines, embeddings, vector stores. Production-grade, not demos. – Frontend · React, Next.js, Angular, TypeScript. Component-driven UIs, accessibility, performance, built to stay fast at year three. – Backend · NestJS, Express, Python (FastAPI / Django). REST and GraphQL APIs, event-driven systems, queues, background workers. – Data · PostgreSQL, MySQL, MongoDB, vector databases. Schema design, indexing, query plans, the unglamorous parts that decide whether the app holds up under real load. – Cloud & DevOps · Azure, AWS, GCP. Kubernetes, serverless, Terraform / Bicep, CI/CD on Azure DevOps and GitHub Actions. Zero-downtime deploys. – Integrations · Stripe, Firebase Auth, Azure AD B2C, messaging, analytics, wired in cleanly, failure paths covered. How I work Direct, written-first, async-friendly across timezones. Long-running, end-to-end engagements are where I do my best work. I plug in, learn the product, and keep it moving. I take on unfamiliar stacks and domains on purpose. That's usually the part I want. If you've got something ambitious, an AI feature you're not sure how to scope, a product that needs to ship with AI baked in from day one, or a vague idea you need someone to think through honestly before writing any code, let's talk.