AI Engineer

La Fosse Associates; City Of London; Hybrid; GBP 120,000 - 138,000; Full time

Job summary

A leading investment organization is seeking an AI Engineer to build its first generation of AI capabilities. This role involves designing AI-powered products and establishing foundational MLOps practices while working closely with the Head of AI. Competitive compensation includes a £120k salary with a 30% bonus and benefits, alongside opportunities for significant influence on early AI strategy.

Benefits

Health insurance

Monthly lunch allowance

High influence on AI strategy

Qualifications

• Strong experience with Azure AI or similar cloud environments.
• Experience productionising LLMs and implementing governance.
• Solid engineering skills with ML frameworks.

Responsibilities

• Build and operationalise AI/LLM solutions using Azure AI.
• Develop agentic workflows using AI frameworks.
• Establish MLOps practices including model deployment and monitoring.

Skills

Building AI/LLM solutions on Azure AI

Implementing RAG pipelines

Python engineering skills

Comfortable with ambiguous environments

Customer-centric problem solving

Tools

Azure Machine Learning

OpenAI GPT models

Job description

AI Engineer

London – 4 Days Onsite
£120,000 + 30% Bonus + Benefits

A fast-growing investment organisation is at the beginning of its Data & AI transformation and is looking for a hands-on AI Engineer to build its first generation of AI capabilities. This is a rare greenfield opportunity to architect and deliver AI solutions using the latest Azure and LLM technologies while shaping how AI is adopted across the business.

The Role

Working directly with the Head of AI, you will design and deliver AI-powered products, build agentic workflows, and establish foundational MLOps practices. You will play a critical role in identifying high-value AI opportunities, translating business requirements into solutions, and leading the organisation through early AI adoption.

Key Responsibilities

• Build and operationalise AI/LLM solutions using Azure AI, Azure Machine Learning, and the wider Microsoft ecosystem.

• Develop agentic workflows using frameworks such as Autogen, Swarm, or LangGraph.

• Design and implement RAG (Retrieval-Augmented Generation) systems and integrate them into business processes.

• Integrate OpenAI GPT models, embeddings, and vector stores into production-grade solutions.

• Deliver early AI/ML use cases (“quick wins”) while shaping the long-term AI platform architecture.

• Establish core MLOps practices including model deployment, monitoring, drift detection, and cost/latency optimisation.

• Support CoPilot adoption and help establish AI governance controls, standards and usage guidelines.

• Collaborate with domain experts to translate requirements into practical AI applications with measurable outcomes.

• Work alongside Data & Platform Engineering to ensure data readiness and platform integration.

What We’re Looking For

• Strong experience building AI/LLM solutions on Azure AI, Azure ML, or similar cloud environments.

• Practical experience implementing RAG pipelines, embeddings, and vector search.

• Exposure to agent-based architectures and workflow orchestration.

• Solid Python engineering skills, including familiarity with ML frameworks and LLM toolchains.

• Experience productionising LLMs, including monitoring, governance and optimisation.

• Ability to operate in ambiguous, low-maturity environments and “figure things out” independently.

• Comfortable working with business teams to uncover opportunities and communicate clearly.

• Financial services experience helpful but not essential.

Soft Skills That Matter

• Customer‑centric and pragmatic problem solver

• Strong communicator able to simplify complex AI concepts

• Consultative mindset with empathy for non‑technical users

• Proactive, autonomous and systems‑oriented thinker

Benefits

• £120k salary + 30% bonus

• Health insurance

• Monthly lunch allowance

• Office‑first hybrid: 4 days a week onsite in London

• High influence on early AI strategy, tooling and architectural choices

• Opportunity to build a first‑of‑its‑kind AI platform from the ground up