Technical Lead, AI Systems Simulation

About CommonAI

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems.

Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing.

The Opportunity

Lead the engineering team building a simulation platform for AI inference systems. You will bring together realistic workloads, hardware models and physical measurements to predict system performance and make the uncertainty in those predictions explicit.

The platform will help engineers and investors assess emerging AI infrastructure, understand design choices, and identify next experiments. You will turn scientific direction into an implementable architecture and delivery plan, help shape recruitment, and develop a team with complementary expertise across software, modelling, measurement and hardware.

You will report to the SIL Scientific Director and line manage a group of engineers in the growing SIL team. Working closely with the Director of Engineering, you will provide daily technical leadership and help shape the team as we recruit. Technical judgement and the ability to bring people with you matter more than having held a particular management title in the past.

What you will do

- Own the simulator codebase, working closely with the Scientific Director, SIL on architectural decisions. Translate the programme's scientific goals into an achievable engineering roadmap.

- Assess existing simulators, serving software and partner components; decide what to reuse, extend or build, and establish interfaces that make the pieces work together.

- Shape recruitment, assess candidates, mentor colleagues and line-manage engineers, building complementary expertise across software, measurement, modelling and hardware.

- Ensure simulator predictions are tested against physical measurements and realistic LLM workloads, with uncertainty made explicit to the people interpreting the results.

- Establish engineering practices for maintainable software, testing, reproducible experiments and effective use of AI coding agents; review designs and results with the relevant specialists.

- Contribute directly to implementation and debugging when engineering coverage is incomplete or a colleague needs support.

An example early project would be to lead a complete study from an investor's question through simulation and measured validation to a useful evidence report, while establishing the team and foundations for subsequent cases.

Requirements

- Substantial industrial engineering experience delivering complex software or hardware/software systems, with clear examples of technical decisions you have owned.

- Depth in at least one of systems simulation, computer architecture, distributed or HPC systems, inference serving, or experimental performance engineering. Experience across more than one is especially valuable.

- Evidence that you can lead people through difficult technical work, explain trade-offs and develop others. This may come from technical leadership and mentoring as well as formal management.

- The judgement to turn high-level scientific direction into independent engineering decisions, and to recognise when wider input is needed.

- Practical engineering ability to review code and designs, investigate failures and help colleagues resolve implementation difficulties.

- Experience using AI coding agents, with the ability to assess their output and help colleagues use them effectively.

Experience connecting research prototypes to maintained engineering systems, collaborating with universities or technology suppliers, and comparing models with measurements would be valuable. We do not expect you to be the deepest specialist in every part of the programme.

Why join us

- Help build UK AI capability and improve how investment and compute serve the public good.

- Build a network spanning UK hardware SMEs, major technology companies, venture and public investors, and leading universities.

- Shape a growing team with startup pace and close academic links.

- Use frontier models and coding agents with a substantial tooling budget.

Benefits

• A collaborative and supportive work environment
• The opportunity to have a high impact in a growing organisation
• Competitive salary package, including pension and benefits
• Professional development opportunities
• Networking opportunities with influential figures from across the tech sector and academia
• A vibrant office environment located a few minutes’ walk away from Cambridge train station

Working with us

Hybrid working, with Cambridge attendance agreed individually around collaboration and job need. We would like you to start as soon as practical and can be flexible for the right person. We value engineering quality and demonstrated leadership over a particular qualification or previous management title.

CommonAI CIC is an equal opportunity employer and is committed to creating an inclusive and diverse workplace.