Key skills
PythonAIRAGAgenticMLOps
About this role
Role Overview
- Design and build agentic AI systems capable of reasoning, planning and goal‑driven decision‑making
- Develop and optimise RAG pipelines, memory strategies, prompts and tool‑use patterns
- Engineer safe‑autonomy designs, including guardrails, human‑in‑the‑loop controls and escalation paths
- Productionise AI agents using Python, DevOps and MLOps practices
- Monitor and improve agent behaviour, performance, drift and risk
- Collaborate with business, data and automation teams to identify high‑value AI use cases
Requirements
- Strong hands‑on engineering experience building production solutions in complex environments
- Demonstrated experience with Python for AI engineering, experimentation and production workloads
- Experience designing or working with agent‑based or autonomous AI systems
- Solid understanding of LLMs, reasoning patterns, RAG, memory and tool orchestration
- Experience deploying AI solutions with appropriate governance, security and risk controls
- Strong analytical thinking, curiosity and ability to work through ambiguity
Tech Stack
- Python
Benefits
- Flexible, hybrid working environment
- Ongoing learning, coaching and training
- Career opportunities across global organisation
- Generous leave entitlements