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 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 should be an exceptional early-career developer who learns quickly and has a strong record of technically demanding builds. 

This is not a role for someone who uses AI without understanding the code or 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.

What You'll Do

• Build and ship features for customer-facing multi-cloud AI compute products 
• Use and develop coding agents for implementation, testing, and documentation day-to-day, with senior review on higher-risk changes 
• Take ownership of the correctness and security of your own code, agent-generated or not 
• Operate within cloud-native systems across multiple providers; diagnose day-to-day issues in Linux, network, container and cloud environments 
• Work with founders, engineers and customers on defined pieces of larger projects, turning clear requirements into shipped code 
• Try out new AI tools as they're introduced and give feedback on what works

How We Work with AI
Agent-assisted engineering is core to the role, not optional. We want engineers who can break ambiguous problems into agent-executable work, give agents the right context and constraints, challenge and verify generated code, and know when to take back control. What you build matters, not how many prompts it took.

Essential

• 1–3 years’ building and shipping real software in a professional setting 
•  AI-native workflow: you use agents actively, can explain where they save you time, and how you verify their output rather than trust it on sight 
• Solid debugging judgment: you can read unfamiliar code, isolate root causes, and assess whether a fix is correct
• Being comfortable in Linux, with some practical exposure to deployment/ops (containers, CI/CD, cloud, IaC, or observability) 
• Someone who takes ownership, has curiosity and clear communication skills 
• Degree-level education in a technical/scientific discipline

Particularly Valuable

• Experience in building backend services, developer tools, or infrastructure products 
• Hands-on experience with Kubernetes, infrastructure-as-code, or working across multiple cloud providers
• Open-source contributions, ambitious personal projects, or other proof of ability outside formal employment (you are welcome to provide links)

• High-impact work on ground-breaking 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