Software Engineer - AI-Native Cloud Infrastructure

CommonAI is building shared infrastructure and products that help organisations develop and deploy deep-tech AI systems.

CommonAI Compute, part of the CommonAI ecosysetm, develops multi-cloud compute products and services for AI teams. We work with commercial, government and research partners to accelerate the adoption of AI across the UK and Europe.

We are a member of the UK government-funded £70 million Scaling Inference Programme, which is advancing AI inference hardware and software infrastructure. CommonAI is also backed by Barclays through programmes focused on deploying AI in regulated markets. Work across these programmes informs and supports our commercial product development.

The Opportunity

We are looking for a capable software engineer who combines strong engineering fundamentals with an enthusiastic, practical approach to AI-assisted development.

You might be an experienced engineer who already uses coding agents extensively, or an exceptional early-career developer who learns quickly and has a strong track record of technically demanding builds. We care more about demonstrated ability, judgement and rate of learning than job titles or years of experience.

This is not a role for someone who uses AI instead of understanding the code. Equally, it is not a conventional development role in which AI is limited to occasional autocomplete. We want engineers who can reason about systems independently, then use agents to explore, implement, test and ship substantially faster.

You will help build customer-facing products for a multi-cloud AI compute ecosystem, working across software development, cloud infrastructure, platform engineering and operations.

What You'll Do

• Design, build and ship customer-facing applications and platforms for multi-cloud AI compute.
• Use coding agents and foundation models throughout the development lifecycle: investigation, design, implementation, testing, review, documentation and operations.
• Take responsibility for the correctness, security and maintainability of agent-generated as well as human-written code.
• Work across application, infrastructure and platform layers, depending on the problem being solved.
• Build and operate cloud-native systems across multiple cloud providers.
• Diagnose problems in Linux, application, network, container and cloud environments.
• Develop effective deployment, testing, observability and reliability practices.
• Work closely with founders, engineers, customers and technical partners to turn incomplete ideas into working production systems.
• Evaluate emerging AI development tools critically, adopting those that produce meaningful improvements in speed or quality.
• Make pragmatic trade-offs between speed, simplicity, reliability and future flexibility.

Senior candidates will also be expected to shape architecture, lead substantial technical decisions and help improve engineering practices across the team.

Requirements

Essential

• Strong programming ability and sound software engineering fundamentals.
• Evidence that you have built, completed and preferably operated meaningful software—not just followed tutorials or assembled demonstrations.
• The ability to understand unfamiliar code, investigate failures and judge whether a proposed solution is actually correct.
• Confidence working in Linux environments.
• Some practical understanding of deployment and operations, such as containers, CI/CD, cloud services, networking, infrastructure as code or observability. We do not expect junior candidates to have mastered all of these.
• Active and enthusiastic use of AI coding tools or agents. You should be able to explain how you use them, where they accelerate you and how you verify their work.
• A habit of testing assumptions and validating generated code rather than accepting plausible-looking output.
• Intellectual curiosity, clear communication and a willingness to take ownership of difficult problems.
  

Particularly valuable

• Experience building backend services, developer tools, infrastructure products or distributed systems.
• Experience with Kubernetes, containers, infrastructure as code or more than one cloud provider.
• Experience operating production systems with demanding reliability, security or observability requirements.
• Open-source contributions, technically ambitious personal projects or other evidence of engineering ability outside formal employment.
• For senior candidates, experience leading projects, making architectural decisions or mentoring other engineers.

You do not need to match every item. We welcome applications from talented engineers at different career stages and will adjust the scope and level of the role to the successful candidate.

Links to code, technical writing, open-source contributions or substantial personal projects are welcome.

Benefits

• High-impact work on important AI and cloud infrastructure problems.
• A collaborative and supportive engineering environment.
• The opportunity to influence products and technical direction at an early stage.
• A competitive salary and stock-option package.
• Professional development and access to a network spanning technology, government and academia.
• A Cambridge office a few minutes’ walk from the railway station, with free snacks and an on-site gym.