AI Engineer

Job Description Roles & Responsibilities Role Overview : The AI Engineer is the primary builder within the AWA AICoE. You will design, build, and test the LangGraph agent graphs, LLM extraction pipelines, prompt management workflows, and MCP tool integrations that power AWA s use cases starting with Intelligent Document Processing (IDP) for cheque clearing and expanding across the bank s operations. You will work directly with the dual-layer orchestration stack (Orkes Conductor + LangGraph) and Azure AI Foundry to deliver production-grade agentic systems. 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 against Use Case Manifest schemas. Prompt engineering and governance: Author, version, and govern prompts through the AWA Prompt Management System (PMS) using semantic versioning; run prompt sensitivity and correctness testing using the AWA IDP Test Strategy. MCP tool integration: Develop and maintain the five core MCP tool servers (query_structured, retrieve_precedents, query_documents, checkpoint_state, observe) and extend them for new use case requirements. Model evaluation and testing: Execute Band 1 and Band 2 testing (Model Testing, Prompt Testing, Agent Testing, AI Security Testing, Adversarial Testing) per the AWA IDP Test Strategy; maintain the Golden Dataset and Regression Dataset. HITL framework: Implement HITL interrupt() calls at mandatory and dynamic review points in LangGraph graphs; configure Orkes Wait tasks; validate HITL 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 at the AWA AI Gateway layer. Cross-field validation rules: Implement business validation rules (amount-words-vs-figures, date validity, MICR format, referential integrity) within LangGraph validation agent nodes. Required Skills and Experience Technical Essential: 5+ years Python development production-grade, not just scripting 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 API (Anthropic, Cohere) Understanding of agent design patterns: ReAct, self-reflection, tool use, HITL REST API development and consumption; JSON schema design Git version control; CI/CD pipeline awareness Technical Advantageous: Experience with Orkes Conductor, Apache Airflow, or Temporal for workflow orchestration Azure AI Document Intelligence or equivalent OCR platform experience Computer vision model integration (object detection APIs) Knowledge of RAG architectures: chunking, vector indexing, Azure AI Search Azure platform familiarity: AKS, ADLS Gen2, Azure ML, Azure Monitor Pydantic, FastAPI, TypeScript/Node.js Domain and Soft Skills: Genuine intellectual curiosity about AI systems and their failure modes Ability to explain AI behaviour to non-technical Ops and business stakeholders Structured problem-solving and debugging approach for non-deterministic AI systems Banking domain interest willingness to deeply understand the business processes being automated Salt is acting as an Employment Business in relation to this vacancy. Desired Candidate Profile 5+ years Python development production-grade, not just scripting 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 API (Anthropic, Cohere) Understanding of agent design patterns: ReAct, self-reflection, tool use, HITL REST API development and consumption; JSON schema design Git version control; CI/CD pipeline awareness Experience with Orkes Conductor, Apache Airflow, or Temporal for workflow orchestration Azure AI Document Intelligence or equivalent OCR platform experience Computer vision model integration (object detection APIs) Knowledge of RAG architectures: chunking, vector indexing, Azure AI Search Azure platform familiarity: AKS, ADLS Gen2, Azure ML, Azure Monitor Pydantic, FastAPI, TypeScript/Node.js Genuine intellectual curiosity about AI systems and their failure modes Ability to explain AI behaviour to non-technical Ops and business stakeholders Structured problem-solving and debugging approach for non-deterministic AI systems Banking domain interest willingness to deeply understand the business processes being automated Company Industry IT - Software Services Department / Functional Area IT Software Keywords AI Engineer Get real-time job updates only on our App