AI Solutions Engineer
Hybrid – London – UK Residents only please – Sponsorship not available.
Salary: £90k - £125k
Build intelligent systems that transform how businesses operate.
We're scaling our AI engineering team to meet demand from enterprise clients who need production-grade intelligent systems. This role combines deep technical work with strategic problem-solving, working at the intersection of cutting-edge AI and real business challenges.
Partner with clients and strategy teams to solve complex business problems. Conduct feasibility assessments and translate ambiguous requirements into clear technical solutions. Engage with domain experts to understand operational constraints.
Shape architecture from discovery through to deployment.
What You'll Build
You'll design and deploy sophisticated AI systems across multiple domains. This includes building LLM applications with robust orchestration, creating multi-agent architectures that handle complex workflows, and implementing advanced retrieval systems using vector databases and embeddings.
You'll work on semantic search pipelines, knowledge modelling, and structured reasoning systems. Your work will integrate with enterprise infrastructure through APIs, automation workflows, and cloud platforms. You'll establish prompt engineering patterns, evaluation frameworks, and safety guardrails that ensure reliability at scale.
What We're Looking For
Self-directed engineers immersed in the AI landscape who drive projects forward and think clearly under uncertainty. You build fast, ship quality work, and communicate technical decisions effectively. You collaborate without ego and obsess over safety and reliability.
You bring 6-8 years of experience in software engineering, AI engineering, or applied data systems. You have substantial hands-on work with LLMs, embeddings, retrieval architectures, and vector stores. Experience with multi-agent systems, orchestration frameworks, or tool-calling patterns is essential.
Strong Python skills are required, along with experience deploying production systems on cloud platforms like Azure, GCP, or AWS. Familiarity with semantic modelling, knowledge graphs, or ontology concepts is valuable.
Most importantly, you can take open-ended problems and rapidly build working prototypes. You're comfortable in client-facing environments and can communicate technical concepts clearly to diverse audiences.
If you like to learn more about the AI Solutions Engineer role – Apply here, or email r.kelly@ltharper.com