Forward‑Deployed AI Engineer
Job Description
The role
The Applied AI team acts as an internal strike force: small, high‑impact groups that embed directly within business units, research groups and platform teams to accelerate the adoption of AI techniques across the firm.
As a Forward‑Deployed AI Engineer you will turn LLM capabilities into production solutions that drive measurable value, from intelligent workflows to research agents.
Your day‑to‑day will alternate between rapid prototyping, integrating with existing systems and coaching domain experts on best practices for maintainable, safe LLM applications. Success is measured by the speed and robustness with which internal partners can ship and own new AI‑based features.
Key responsibilities of the role include:
Engaging directly with internal clients to understand pain points, identify AI opportunities and shape solution roadmaps
Building end‑to‑end AI‑powered systems in Python using LangGraph, and similar orchestration frameworks, FastAPI, MCPs and vector‑based retrieval services
Fine‑tuning and optimising models (parameter‑efficient or full‑weight) to meet domain‑specific accuracy, latency and cost targets
Designing RAG and agentic workflows that safely combine proprietary data with public and on prem models
Integrating new services with existing C#, C++ or JVM‑based stacks, ensuring clear APIs, monitoring and CI/CD pipelines.
Establishing repeatable patterns, such as reference architectures, templated infra testing harnesses, that enable teams to self‑serve future use‑cases
Upskilling engineers and analysts through pair‑programming, workshops and written playbooks on AI engineering best practices
Staying on top of the LLM ecosystem, including tooling, evaluation techniques and open‑source releases, and feeding lessons learned back into the wider AI Engineering Department
