CommonAI CIC
Software Engineer - AI-Native Cloud Infrastructure
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CommonAI is building shared infrastructure and products that help organizations develop and deploy deep-tech AI systems.
CommonAI Compute, part of the CommonAI ecosystem, 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
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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
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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
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