AI Engineer (Consultant)
Remote-first · Full-time (UK) · £80k–£110k+ DOE
We are looking for an experienced AI engineer to help our clients design, build, and operate production-grade AI systems — from agents and automation to the infrastructure and security they depend on.
You will be part of a small, senior team that moves between strategy and implementation: helping shape client roadmaps, then dropping into the code, data, and infrastructure to make it real.
Role overview
You will work closely with founders, product teams, and security stakeholders to turn ideas into robust systems. The work is hands-on and ranges from architecture and implementation to debugging, optimisation, and hardening across cloud infrastructure and AI products.
On a typical week you might be pairing with a client team on an LLM-powered feature, shaping an AI architecture or evaluation approach, and then dropping down into code (Python, TypeScript, SQL) to ship, test, and productionise it. You will often be the person who “figures it out” when something odd happens in production, or when a team is unsure how to take an AI idea from prototype to something reliable.
Because we work with a small number of clients, you will have input into what we work on, how we structure projects, and how we improve our internal tooling and approaches over time. You will help us decide when to move fast with pragmatic solutions and when to invest in more rigorous evaluation, hardening, and documentation.
What you might work on
- Designing and implementing AI agents and autonomous workflows.
- Building secure LLM integrations, tooling, and internal APIs.
- Developing and hardening RAG pipelines and data access controls.
- Improving observability, evaluation, and safety guardrails for AI systems.
- Modernising infrastructure, CI/CD, and deployment workflows for AI workloads.
- Helping client teams debug tricky production issues across model behaviour, data, and infrastructure.
About you
- Strong software engineering background (Python or similar, with experience shipping and operating production systems).
- Hands-on experience with modern AI tooling (LLMs, vector stores, agents, or similar), ideally including prompt design and evaluation.
- Comfortable working across infrastructure, APIs, and application code (for example: cloud platforms such as AWS/GCP/Azure, containers, CI/CD, observability).
- Security-minded: you think about failure modes, abuse cases, and guardrails when designing systems and workflows.
- Clear written and spoken communication; able to work directly with clients and explain trade-offs in plain language.
- Happy working in a small, senior team with a high degree of autonomy and ownership.
Technologies we often touch
This is not a checklist, but some of the technologies you are likely to see in the work:
- Python and TypeScript for back-end services, internal tools, and automation.
- LLM providers (for example OpenAI, Anthropic, or open-source models) and orchestration frameworks.
- RAG pipelines and vector databases (such as pgvector, Pinecone, or similar systems).
- Cloud infrastructure (AWS, GCP, or Azure), Docker/Kubernetes, and CI/CD pipelines.
- Monitoring, logging, and security tooling for production systems.
How to apply
Send an email about your background, links to anything you are proud of (GitHub, projects, or writing) and your CV.