AI Forward Deployed Engineer

Leading Buy Side Client | London | Hybrid | Competitive Daily Rate

The Opportunity

Join a leading Buy Side Client building production AI systems that transform how investment professionals work. This isn't an R&D role—you'll ship LLM-powered applications that investment and finance teams depend on daily, while simultaneously building the governed AI platform that underpins the entire organisation.

50% embedding with business teams | 50% platform engineering

What You'll Build

Embedded AI Applications:

1. Ship high-value LLM applications directly with Investment and Finance teams
2. Turn ambiguous business problems into production-grade AI solutions
3. Deploy agentic workflows using Claude and ChatGPT APIs
4. Work alongside investment professionals to identify and solve real problems

AI Platform Engineering:

1. Build and extend governed AI platform: LLM gateway, model control layer, privacy proxy
2. Develop MCP connectors for Salesforce, M365, deal flow systems, analytics platforms, and third-party data providers
3. Implement logging, audit trails, observability, and evals tooling
4. Design agentic workflows spanning multiple systems with proper tracing, scoring, and regression checks
5. Ensure compliance with regulatory requirements (FCA, DORA)

Essential Skills:

Production AI Engineering:

1. Deep practical fluency with Claude and ChatGPT APIs, tool use, structured outputs, and prompting techniques
2. Track record shipping LLM-powered applications that users depend on
3. Experience with LLM gateways, privacy proxies, agent observability, or evals frameworks (even at hobby/prototype level)

Software Engineering:

1. Strong Python and TypeScript for production systems
2. Modern Azure infrastructure and services
3. Integration patterns: REST APIs, MCP, webhooks, SSO/Entra ID
4. Production code experience in regulated or enterprise environments

Business & Communication:

1. Excellent communicator who can sit with investment professionals and turn conversations into code
2. Ability to work with ambiguous business problems and ship concrete solutions
3. Experience pairing with non-technical stakeholders