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Role Overview

Key Responsibilities

• Agent graph development: Design and implement LangGraph agent graphs for Supervisor-Worker orchestration, self-reflection, actor-critic, and HITL interrupt patterns using TypedDict state schemas and conditional edge routing.
• LLM extraction pipeline: Build and maintain LLM-based entity extraction pipelines using Azure AI Foundry, implementing structured output enforcement, per-field confidence scoring, and Pydantic output validation.
• Prompt engineering and governance: Author, version, and govern prompts through the AWA Prompt Management System using semantic versioning; run prompt sensitivity and correctness testing.
• MCP tool integration: Develop and maintain core MCP tool servers and extend them for new use case requirements.
• Model evaluation and testing: Execute multi-band testing (Model, Prompt, Agent, AI Security, Adversarial) per the AWA IDP Test Strategy; maintain Golden Datasets and Regression Datasets.
• HITL framework: Implement Human-in-the-Loop interrupt calls at mandatory and dynamic review points in LangGraph graphs; configure wait tasks; validate state persistence and checkpoint-based resumption.
• AI guardrail integration: Integrate Azure AI Content Safety, PII detection and tokenisation, prompt injection shielding, and output sanitisation into agent pipelines.
• Cross-field validation rules: Implement business validation logic within LangGraph validation agent nodes.

Required Skills & Qualifications

• 5+ years of Python development in production environments.
• Hands-on experience with LangGraph, LangChain, or equivalent agentic AI frameworks.
• Practical LLM prompt engineering: structured outputs, few-shot design, output schema enforcement.
• Familiarity with Azure AI Foundry / OpenAI API or equivalent LLM APIs (Anthropic, Cohere).
• Understanding of agent design patterns: ReAct, self-reflection, tool use, and HITL.
• REST API development and consumption; JSON schema design.
• Git version control and CI/CD pipeline awareness.
• Bachelor's degree in Computer Science, AI/ML, Software Engineering, or related field.

Preferred Attributes

• Experience with Orkes Conductor, Apache Airflow, or Temporal for workflow orchestration.
• Azure AI Document Intelligence or equivalent OCR platform experience.
• Knowledge of RAG architectures: chunking, vector indexing, Azure AI Search.
• Azure platform familiarity: AKS, ADLS Gen2, Azure ML, Azure Monitor.
• Pydantic, FastAPI, and/or TypeScript/Node.js proficiency.
• Master's degree or equivalent research/industry experience.
• Relevant Azure certifications (AI Engineer Associate, Developer Associate).
• Genuine intellectual curiosity about AI systems and their failure modes.