We use AI to modernise legacy code

Tl;dr

We're combining LLMs and transpilers to translate COBOL into Java. If you’re getting into (or already work in) Rust, and have a strong product mindset, this role could be a great fit. Come and build LLM pipelines and agents, that help the largest companies modernise their legacy codebases.

Background

All large companies are stuck with legacy code running critical systems, written in languages that are dying and running on architectures that are increasingly expensive to maintain.

Our code translation pipeline automates the menial task of converting code from one language to another.

Previously human engineers would have had to read the legacy code and translate the codebase by hand, file by file, into the target language.

We're pioneering a novel approach to this problem, and leveraging LLMs to produce readable code in a fraction of the time.

What’s the role?

AI Agents are currently the bleeding edge of applied AI research, and you may have seen projects like Devin, OpenDevin, SWE-Agent, or GitHub Copilot Workspace.

This role is to build an AI Agent to perform refactoring of the transpiled code, that could only be possible with an LLM.

You’ll need to collaborate with a small but talent-dense team to design and implement the AI Agent.

You'll love what we're working on if you're interested in:

• LLM Agents
• New LLM models and architectures
• Data curation, generation, and even some fine-tuning
• Programming languages and compilers

You'll be joining a small group of engineers who are obsessed with the challenges posed by code translation, and who want to build tools to improve the process of writing and maintaining software.

Key requirements

• Must have mastered a non-Rust product language (e.g. TypeScript, Java, C++, Go, etc…)
• Must have nailed Rust fundamentals, at a minimum in your personal projects
• Hands on experience with the state of the art LLMs
• Strong fundamental understanding of LLM pipelines and agents

Also nice to have (bonus points)

• Experience evaluating LLM pipelines
• Experience fine-tuning models (e.g. PyTorch/Axolotl)
• Understanding of programming language design

Benefits and Perks

• Up to ~0.5% options
• Competitive salary
• 25 days holiday, in addition to bank holidays
• Top tier private medical insurance