Full-Stack AI Engineer (Prompt Engineering & Agentic Systems) Python, Azure

Responsibilities

• Design, test, and optimize 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.

• Build and maintain 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 via 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, Key Vault, secrets management, and runtime policies.
• Optimize cost, performance, observability, and reliability.

• Build and maintain 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 business needs into measurable AI workflows.
• Partner with security, engineering, and product teams.
• Produce clear documentation (architecture, prompts, runbooks).
• Act as an internal SME for agentic systems and modern AI development patterns.

Required Skills

• Advanced prompt engineering (Gemini, GPT, Claude; multi-model systems).
• Strong Python, FastAPI, async programming.
• Deep experience with Azure cloud services and serverless patterns.
• Hands-on RAG and vector databases (Azure Search, Pinecone, FAISS, etc.).
• Agent frameworks (LangChain, LlamaIndex, AutoGen, or custom).
• Frontend experience with React + TypeScript.
• Strong 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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.