AI Engineer

5 months ago

London, United KingdomSenior

Responsibilities

Design and build LLM-driven agents for planning, optimization, and decision-making workflows.
Develop agent orchestration patterns involving tools, memory, evaluation, and guardrails.
Build and maintain RAG pipelines, structured prompting, and retrieval strategies.
Use synthetic data, scenario replay, state machines, and simulation to design and validate product logic.
Build end-to-end product features across Python and TypeScript backend services, REST and GraphQL APIs, and React frontend experiences.
Create human-in-the-loop interfaces for AI review, override, and explainability.
Own production services, including performance, reliability, observability, security, testability, compliance, and cost.
Use infrastructure-as-code and modern CI/CD practices while collaborating with Product, Design, and engineering teams.

Strong full-stack engineering background with deep backend capability.
Production experience with Python and/or TypeScript and experience owning systems from concept to production.
Hands-on experience with LLMs, modern AI tooling, RAG systems, embeddings, vector search, and agentic patterns such as tools, planners, and evaluators.
Experience productionizing ML or AI systems, including monitoring, failure-mode management, and iterative improvement.
Comfort working in small, high-ownership teams and operating with ambiguity.
A practical, agent-first, spec-driven, or simulation-led engineering mindset.
Strong collaboration skills and a bias toward shipping, learning, and iterating.
Preferred experience includes logistics, optimization, simulation-heavy domains, data engineering, ML platforms, developer tools, internal platforms, or regulated and security-conscious environments.

Flexible and hybrid work opportunities are available to support different needs and lifestyles.
The role offers an inclusive, collaborative workplace with opportunities to engage with colleagues and build community.

5,001-10,000 employees