Generative AI Engineer
Build production-grade RAG pipelines, agentic workflows, and internal AI platforms using Python, FastAPI, LangGraph/LangChain, vector/graph databases, OpenAI/Anthropic, and Azure AI. This is the first dedicated AI engineering hire at a global investment business managing tens of billions in assets.
Free Tailor for ATS: 10/10 runs left
Founding AI Engineer — Build an AI Capability From the Ground Up
A leading global investment business is looking to make its first dedicated AI Engineering hire — a rare opportunity to build and shape AI capability from day one inside a highly respected organisation managing tens of billions in assets.
This is far beyond experimentation or internal demos. The successful candidate will design, build, and own production-grade AI systems that solve real business problems — from advanced RAG pipelines and agentic workflows to internal AI platforms used across the organisation.
This role offers genuine autonomy, visibility, and the chance to influence AI strategy, architecture, and engineering standards at an early stage.
Why this opportunity stands out
Foundational AI hire with significant ownership and influence
Greenfield environment with freedom to shape tooling, architecture, and best practices
Direct exposure to complex, high-value datasets and workflows
Strong long-term investment and commitment to AI from leadership
Opportunity to build systems with immediate, measurable impact
The role
Build production-grade RAG pipelines across complex unstructured data
Design and deploy multi-agent AI systems and orchestration frameworks
Integrate LLMs across OpenAI, Anthropic, and open-source ecosystems
Develop semantic search, vector database, and graph-based retrieval systems
Own AI evaluations, observability, governance, and reliability
Build internal AI products that enhance decision-making and operational efficiency
The ideal profile
Proven experience shipping production AI/LLM systems used by real users
Strong end-to-end engineering capability — from architecture through deployment
Deep Python and backend engineering experience
Strong understanding of modern AI tooling, RAG, and agentic systems
Comfortable operating in ambiguity and building from scratch
Uses AI tooling aggressively, but critically and responsibly
Cares about product quality, reliability, and business outcomes — not just models
Tech environment
Python • FastAPI • LangGraph/LangChain • Vector Databases • Graph Databases • OpenAI/Anthropic • Azure AI • RAG • Agentic Systems • APIs • CI/CD • Cloud Infrastructure
London | Senior / Principal Level
This is an exceptional opportunity for an ambitious AI Engineer looking to build something meaningful at the frontier of applied AI — with the autonomy, backing, and technical scope to make a genuine impact.