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Open nowPosted 53 days ago

Senior Software Engineer - AI-Native Cloud Infrastructure

Workable (global search)108,016 open roles

Where
Cambridge, England, United Kingdom
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Your applicationOpen nowSenior Software Engineer - AI-Native Cloud InfrastructureWorkable (global search) · Cambridge, England, United Kingdom

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 53 days ago

Workable (global search) median: 7 days open

The posting

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 experienced developer who already uses coding agents 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

  • Design, build and ship customer-facing multi-cloud AI compute products
  • Develop coding agents across the full lifecycle: investigation, design, implementation, testing, review, documentation and ops
  • Take ownership of the correctness and security of your own code, agent-generated or not
  • Build and operate cloud-native systems across multiple providers; diagnose issues in Linux, network, container and cloud environments
  • Work directly with founders, engineers and customers to turn incomplete ideas into production systems
  • Critically evaluate new AI tools and adopt what actually matters in the industry
  • Shape architecture, lead substantial technical decisions and help improve engineering practices across the team

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.

Requirements

Essential

  • Strong engineering fundamentals: evidence you've built and shipped real software
  • 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
  • Sharp debugging judgement: 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)
  • Clear communication skills, ability to work under minimal supervisionDegree-level education in a technical/scientific discipline

Particularly Valuable

  • Experience in leading projects, making architectural decisions and mentoring of junior engineers
  • Experience in building backend services, developer tools, infrastructure products or distributed systems
  • Deep knowledge of Kubernetes, infrastructure-as-code, or multi-cloud architecture at production scale
  • Exposure to production systems with demanding reliability/security requirements
  • Open-source contributions, ambitious personal projects, or other proof of ability outside formal employment (you are welcome to provide links)

Benefits

  • 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
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