AI Software Engineer

Harrington Starr; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Harrington Starr is seeking a strong Software Engineer to join as one of the first technology hires in an early-stage hedge fund within an established asset management business. You will work across the platform, building research tools, backend services, data pipelines and AI-enabled applications used directly in the investment process.

You’ll contribute across the stack, with a focus on robust software that supports LLM and RAG capabilities, containerised with Docker and Kubernetes, and

Qualifications

• Strong software engineering fundamentals with production-grade systems experience.
• Experience building APIs, services and data pipelines.
• Experience with LLMs, RAG or AI applications.
• Familiarity with Docker, Kubernetes and cloud environments.

Responsibilities

• Build research and screening tools, backend services, data pipelines and AI-enabled applications used in investment workflows.
• Own the software you build in a fast-moving startup environment.
• Collaborate across the platform team and wear multiple hats as needed.

Skills

C#/Java/Python/Go

Tools

APIs & Data Pipelines

Docker

Kubernetes

Cloud

Job description

I’m working with an early-stage start-up being built within an established asset management business, creating a new AI-enabled hedge fund.

They’re keeping the team deliberately small and are looking for a strong Software Engineer to join as one of the early technology hires.

You’ll be working across the platform, building research and screening tools, backend services, data pipelines and AI-enabled applications used directly within the investment process. They already have LLM and RAG capabilities in place, so this isn’t a pure AI Engineer role. They need someone with strong software engineering fundamentals who can build production-grade systems around the AI.

What they’re looking for:

• Background in C#, Java, Python or Go
• Experience building APIs, services and data pipelines
• Experience with LLMs, RAG or AI applications
• Docker, Kubernetes and cloud experience would be useful
• Comfortable working in a fast-moving start-up environment
• Someone who wants to stay hands-on and take ownership of what they build

Hedge fund experience isn’t essential. They’re more interested in finding a strong engineer who has worked in an environment where they’ve had to wear different hats, solve problems and get things into production.