Principal AI Engineering Lead

What you will do

• Own End-to-End AI Engineering Delivery: Design, build, and deploy production‑grade AI/ML systems (LLMs, agents, predictive models) across the full lifecycle, including data ingestion, model integration, evaluation, and ensuring production readiness within a regulated environment.
• Develop Reference Architectures & Accelerators: Create reusable frameworks, SDKs, and reference implementations (e.g., agent orchestration patterns, prompt frameworks, RAG pipelines) to standardise AI development across engineering teams.
• Hands‑on Engineering Leadership: Contribute directly to codebases (Python, APIs, orchestration layers), perform code reviews, and enforce engineering standards across AI, data, and application layers.
• Implement AI‑Native Development Patterns: Drive adoption of advanced engineering practices including LLM‑based development workflows, autonomous agents, retrieval‑augmented generation (RAG), and AI‑augmented CI...