Senior Software Engineer - Applied AI

About the role

At CoMind, we are developing a non-invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting-edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world.

THE ROLE:

You will build the platform that transforms raw neuro-signals into longitudinal patient insights, effectively defining the new standard of care in neuro-critical settings.

As a Senior Software Engineer within the CoVision project, you will play a central role in developing, maintaining, and optimising the Large Language Model software deriving actionable intelligence in our fleet of neuromonitoring products. You will bridge the gap between advanced AI research and production-ready, regulated medical software, ensuring software reliability across our deployed fleet.

At CoMind, all team members work at least 4 days per week from our new Kings Cross offices, plus a flexible work-from-home day.

RESPONSIBILITIES:

- AI Integration: Integrate an on-device LLM into the CoMind One system, connecting it to live neuromonitoring signals and building the query and response layer clinicians interact with.

- Model Evaluation & Reliability: Own how we measure whether the model answers the right clinical questions correctly and consistently. Build the evaluation, prompting and guard-rail approaches that keep output safe to show at the bedside.

- Systems Performance: Optimise inference performance on constrained on-device hardware, managing latency, memory and throughput within the CoMind One system.

- Medical Device Software Development: Design and develop medical device software to IEC 62304 and ISO 14971, from real-time on-device behaviour through to the interfaces clinicians touch.

- Compliance & Cybersecurity: Ensure AI deployments meet cybersecurity requirements and regulatory standards, including FDA guidance for AI/ML-enabled devices.

- Reliability & Collaboration: Keep the deployed fleet reliable, and work directly with hardware, product and clinical teams to diagnose and resolve issues quickly.

- AI is fundamental to our culture — it's not just a tool, but a core part of how we work, collaborate, and innovate. We expect all team members to embrace AI in their daily work and continuously find new ways to use it effectively.

SKILLS & EXPERIENCE:

- 7+ years of hands-on software engineering.

- Comfortable working in C++, with Python alongside it.

- Practical experience using LLMs as an applied tool: prompting, guardrails, RAG, evaluation, and reasoning about model behaviour.

- You've built, or extended a model and integrated it meaningfully into a real product, close to the surface users actually touch.

- Experience integrating third-party libraries or complex components into a larger system, ideally performance-sensitive or resource-constrained.