About the role
team.blue is building an AI layer across its digital-services ecosystem, and this role combines production AI engineering with technical direction. The work spans multi-agent orchestration, voice AI, retrieval-augmented generation, model fine-tuning, evaluation, and inference serving. You would also build data and feature pipelines and establish observability, reliability, and deployment practices for AI systems.
The position sets architectural standards across the group, leads design reviews, and mentors ML engineers and applied scientists. It also involves translating product and commercial needs into ML problems with measurable outcomes, while tracking research and deciding what is ready for production.
Highlights
- Architect agent orchestration, tool-use, and voice AI systems.
- Fine-tune and evaluate LLMs for customer support and structured tasks.
- Own AI observability, guardrails, and production reliability.
- Set technical direction and mentor engineers and applied scientists.
This recap is dataskew's editorial summary, not the company's copy.