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Software Engineering Manager (Test & Devops)

Comind · London, UKsenior

In short

  • ▸Liderazgo técnico de equipos de pruebas y DevOps en un dispositivo médico regulado.
  • ▸Gestión de CI/CD, infraestructura embebida (Yocto), y validación continua con enfoque en seguridad y cumplimiento.
  • ▸Destacado: Trabajar en un entorno de alta regulación (IEC 62304 Clase C) con enfoque en inteligencia artificial y cumplimiento automatizado.

Proficiency in English is required for collaboration across global teams.

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What they ask for

  • ✓10+ años de experiencia en software, DevOps o pruebas, con 3+ en liderazgo técnico.
  • ✓Experiencia comprobada liderando equipos de DevOps, pruebas o infraestructura.
  • ✓Conocimiento sólido en CI/CD, automatización de pruebas y sistemas embebidos.
  • ✓Experiencia con Yocto o plataformas embebidas Linux basadas en BSP.
  • ✓Conocimiento de estándares reguladores (IEC 62304, ISO 14971) en dispositivos médicos.
  • ✓Habilidades avanzadas en Python, C/C++, y cloud (AWS/GCP/Azure) con IaC.

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YoctoCI/CDDevOpsTest AutomationEmbedded LinuxPythonC/C++AWSGCPAzure

Who should you write to at Comind?

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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: The Software team at CoMind spans the full stack of a regulated medical device company — from embedded and real-time systems through application software, ML inference, GUI, DevOps, and test engineering. It is a team that builds across every layer, working to medical device software standards and shipping software that has to perform reliably in clinical environments. This is a people-first leadership role. You will manage and develop a team of test and DevOps engineers, set priorities and development plans, and drive performance, while staying hands-on in the technical direction. At CoMind, all team members work at least 4 days per week in the office, plus a flexible work-from-home day. This role is based in our London (Kings Cross) office. Responsibilities: Manage and mentor a team of DevOps and test engineers, setting priorities, individual development plans, conducting performance reviews, and maintaining a high standard of engineering practice Own the CI/CD strategy and build and release infrastructure across the software stack, including the multi-device test fleet, pipeline reliability, and artifact management Own the Yocto-based embedded Linux platform build and deployment, including the signed software update mechanism with rollback, hardware compatibility checks, and image integrity and authenticity Lead architecture reviews, perform proofs-of-concept for new infrastructure tools, and contribute directly to codebases where high-level technical hurdles require expert intervention. Define and drive the software V&V and test automation strategy, building infrastructure for continuous validation and championing design for testability across the engineering stack Establish compliance-as-code workflows that map verification evidence to IEC 62304 (Class C) and ISO 14971 risk controls, maintain the high-bar for engineering excellence in a regulated safety-critical environment and automate regulatory evidence generation to reduce time to submission Own cloud-side data pipelines and infrastructure-as-code, supporting data ingest, analysis, and MLOps workflows where required Coordinate cybersecurity workstreams, working closely with IT and QARA teams Partner with the Software Engineering Manager on release processes, branching strategy, and automated quality gates 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. Nice to have: Experience with hardware-in-the-loop or software-in-the-loop test environments Exposure to MLOps, including model drift validation, dataset governance, and automated performance evaluation and deployment of organisational AI strategy Experience with cybers

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