Gen AI Full-Stack Engineer

Responsibilities

• Design, test, and improve enterprise-grade prompts, system instructions, schemas, and agent workflows.
• Build multi-step agentic pipelines, self-refining loops, and deterministic fallback logic.
• Implement PromptOps: versioning, evaluations, regression testing, hallucination mitigation, token optimization, and governance.
• Build RAG pipelines, vector search, memory layers, and grounding strategies.
• Develop Python-based microservices (FastAPI, async patterns, REST APIs).
• Deliver full-stack AI applications (React, TypeScript) used by analysts for multi-turn AI interactions.
• Manage GitHub, CI/CD, testing, branching, and release automation.
• Integrate AI services through serverless, containerized, and event-driven architectures.
• Deploy AI workloads on Azure App Services, Functions, AKS, Logic Apps, Event Grid.
• Implement IaC using Azure Bicep / ARM.
• Enforce security, RBAC, Vault, secrets management, and runtime policies.
• Increase cost, performance, observability, and reliability.
• Build embeddings, feature pipelines, telemetry, and drift detection.
• Perform data analysis and experimentation using KQL and Splunk SPL.
• Support model selection, fine-tuning strategies, safety constraints, and evaluation frameworks.
• Translate ambiguous needs into measurable AI workflows.
• Partner with security, engineering, and product teams.
• Produce clear documentation (architecture, prompts, runbooks).
• Be an internal subject matter expert for agentic systems and modern AI development patterns.

Requirements

• Advanced prompt engineering (Gemini, GPT, Claude; multi-model systems).
• Python, FastAPI, async programming.
• 5+ years experience with Azure cloud services and serverless patterns.
• Hands-on RAG and vector databases (Azure Search, Pinecone, FAISS).
• Agent frameworks (LangChain, LlamaIndex, AutoGen, or custom).
• Frontend experience with React + TypeScript.
• CI/CD, GitHub Actions, and DevOps practices.
• Multi-agent or autonomous systems experience.
• AI in security operations or automation.
• Azure / ML Ops certifications.
• SOC2 / ISO / AI governance exposure.
• Open-source or AI tooling contributions.