AI / ML Engineer

Role overview Join an engineering team where artificial intelligence is the foundation of the work, not an add-on. The role focuses on designing and shipping agentic AI systems, LLM-powered workflows, and machine learning infrastructure for enterprise clients across multiple industries. You will operate as a hands-on builder who has already taken AI products from prototype to reliable production.

Responsibilities - Design, build, and deploy LLM-powered systems and autonomous AI agents that reach real production environments rather than stopping at proofs of concept - Build and maintain retrieval-augmented generation pipelines, covering document processing, vector database management, embedding strategies, and retrieval optimisation - Partner with clients and internal stakeholders to choose the right technical approach for AI-augmented workflows, including recommending alternatives when LLMs are not the right fit - Fine-tune and evaluate language models for domain-specific use cases, and create evaluation frameworks that measure outcomes that actually matter - Develop the production infrastructure that keeps AI systems observable, including logging, monitoring, cost tracking, and failure detection for probabilistic pipelines - Contribute to internal frameworks and tooling that accelerate and standardise how new client AI systems are spun up

Requirements - Three or more years of applied machine learning or AI engineering experience, with concrete examples of systems shipped to real users in production - Hands-on experience working with LLM APIs and agent frameworks - Understanding of how to make AI systems production-ready, including latency management, cost control, fallback handling, and effective monitoring - Familiarity with fine-tuning workflows and the trade-offs between fine-tuning, prompt engineering, and RAG for different scenarios - Comfort staying current with new model releases, emerging frameworks, and relevant research

Nice to have - Experience working with enterprise clients or in a consulting context, particularly where data privacy requirements were part of the work

Benefits and work setup - Full-time, remote position - A portion of company invoicing is directed to charitable causes, so day-to-day work contributes to real-world impact automatically