Software Engineer

nahc.io; Greater London; On-site; GBP 100,000 - 180,000; Full time

Job summary

nahc.io in London is seeking a Staff Software Engineer to help turn advanced research into robust, production‑quality software. You will collaborate with researchers and engineers to design core platform components, build backend services and drive scalable, concurrent workloads.

This role emphasizes architectural decisions, reliability and performance as the system handles large-scale reasoning tasks. Strong ownership and code quality will be essential as production-grade inference workloads

Qualifications

• Master's degree in CS or equivalent practical experience.

Responsibilities

• Designing and building core components of the platform.
• Developing backend services and APIs.
• Contributing to algorithms and AI capabilities.
• Translating research concepts to production-grade software.
• Designing systems for large-scale reasoning and inference workloads.
• Working with concurrent, parallel and distributed systems.
• Making architectural decisions around performance and reliability.
• Writing well-tested, maintainable code and participating in design reviews.
• Shaping how AI-assisted development tools are used across the org.

Skills

Rust

Elixir

Python

Java

C

F#

Haskell

Distributed systems

Cloud platforms

Education

Master's degree in Computer Science or related

Tools

AWS

Google Cloud

Azure

Job description

We’re working with an early-stage, well-funded stealth AI company developing a new generation of reasoning technology.

The team brings together experience from frontier AI research, enterprise software, biotech, defence and aerospace, and is tackling some genuinely difficult problems at the intersection of AI, software engineering and large-scale computation.

They’re now looking for a Staff Software Engineer to join the London team and play a key role in turning cutting-edge research into robust, production-quality software.

This is a role for someone who enjoys getting deep into technical problems - whether that means designing systems, working on algorithms, solving concurrency challenges, or figuring out how to make complex workloads reliable at scale.

What you will do:

You’ll work closely with researchers, infrastructure engineers and application specialists, helping bridge the gap between research and production.

Your work will include:

• Designing and building core components of the company's software platform
• Developing backend services, APIs and supporting infrastructure
• Contributing to algorithms and the implementation of novel AI capabilities
• Translating research concepts and prototypes into maintainable, production-ready software
• Designing systems capable of handling large-scale reasoning and inference workloads
• Working with concurrent, parallel and distributed systems
• Making architectural decisions around performance, reliability and scalability
• Writing well-tested, maintainable code and contributing to engineering standards
• Participating in code reviews and technical design discussions
• Helping shape how AI-assisted development tools are used across the engineering organisation

What you will need:

• A Master's degree in Computer Science, Computer Engineering or a related technical field, or equivalent practical experience
• Strong professional software engineering experience, with evidence of taking significant technical ownership
• Excellent proficiency in at least one modern programming language — examples include Rust, Elixir, Python, C, Java, F#, Haskell or similar
• Strong foundations in software design, including both functional and object-oriented approaches
• Experience designing and building concurrent, parallel or distributed systems
• Experience working with a major cloud platform such as AWS, Google Cloud or Azure
• A strong interest in software architecture, algorithms and solving technically challenging problems
• Hands-on experience with modern AI coding assistants such as Claude or Codex

Nice-to-haves:

• Experience with AI, machine learning or scientific computing
• Experience working on inference, optimisation or other computationally intensive workloads
• Previous experience in an early-stage startup
• Experience working effectively in a distributed or remote engineering environment
• DevOps / platform engineering experience
• Experience taking research or experimental software and turning it into reliable production systems