Full Stack AI Engineer

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.

3+ years building production software, including full-stack applications and/or AI-enabled systems.

Experience contributing to user-facing AI product features, from backend through frontend.

Experience with agentic systems in production or pre-production (tool calling, multi-step workflows, RAG, structured outputs).

Exposure to evaluation frameworks such as golden datasets, regression gates, or CI quality controls.

Hands-on experience with .NET Core, ASP.NET Core Web API, SQL, and Microsoft technologies.

Frontend skills in React and/or Next.js, TypeScript, component-based UI, API integration, and state management.

Experience building tables, document-centric interfaces, review flows, or streaming experiences.

Understanding of UX patterns for AI systems (confidence, citations, fallbacks, edit/retry, human review).

Python proficiency, including FastAPI, Pydantic v2, async patterns, and pytest.

Hands-on experience with LangChain and/or LangGraph: stateful graphs, tool integration, checkpointing, and streaming.

Prompt engineering skills: structured output design, system prompt construction, and multi-turn context management.

Experience with RAG pipelines and familiarity with vector databases such as pgvector and/or OpenSearch.

Familiarity with LLM evaluation: golden dataset design, metric definition, and regression gates.

Awareness of context window management strategies.

Regular use of AI coding assistants (Cursor, GitHub Copilot), with good judgement about where generated code is reliable and where it needs scrutiny.

Familiarity with multi-agent concepts: orchestration logic, tool interfaces, and failure-handling patterns.