AI Automation Engineer

Role & responsibilities

The AI Automation Engineer supports the Delivery Transformation Office in identifying, designing, developing, deploying, and supporting AI-led automation solutions across delivery programs. This is a fully hands-on engineering role the successful candidate personally owns the complete journey from use-case discovery through architecture, development, testing, deployment, and production stabilization.

This is not a coordination, governance, or proof-of-concept-only role. You will write code, build integrations, create AI agents, troubleshoot failures, deploy applications, and keep solutions stable in production.

Preferred candidate profile

• Strong hands-on Python development and automation engineering able to independently build and deploy production-grade applications.
• Practical experience with Generative AI, LLM APIs, prompt engineering, structured outputs, and tool calling; hands-on with Claude, Claude Code, or equivalent tools.
• Experience building AI agents or multi-step agentic workflows.
• Strong REST API, JSON, authentication, and enterprise integration skills.
• Solid SQL and data-processing capability; experience with browser or desktop automation.
• Strong knowledge of Git, Docker, CI/CD, automated testing, and production troubleshooting.
• Experience deploying solutions into cloud or enterprise environments.

Preferred

• LangGraph, Semantic Kernel, AutoGen, Claude Code, or similar agent frameworks.
• Vector databases, embeddings, semantic search, and RAG pipeline design.
• React, JavaScript, or TypeScript; Redis, Celery, ARQ, or event-driven processing.
• OCR, document intelligence, multimodal AI; Kubernetes or serverless deployment.
• AI evaluation, agent tracing, and LLM observability tooling.