Senior Software Engineer - Applied AI

Jackalope Digital LLC

Greater London

Hybrid

GBP 94,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Equity in the company

Salary-sacrifice pension scheme

Private medical, dental and vision

Group life assurance (4x annual income

Mental health support (1:1 sessions)

Unlimited holiday + quarterly remote

Lunch voucher (£10) + free dinner on晚

Fresh fruit deliveries & snacks

YuLife wellness discounts

Job summary

CoMind is building non-invasive neuromonitoring technology to improve brain disorder diagnosis and treatment. As a Senior Software Engineer on the CoVision project, you will integrate an on-device LLM, ensure safety and reliability, and optimize performance for constrained hardware in a regulated medical context.

You will work from our Kings Cross offices at least 4 days a week with a flexible remote day, collaborating with hardware, product and clinical teams to deliver clinically impactful

Qualifications

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.
Comfortable reasoning about performance: latency, memory and throughput on constrained hardware.
Strong with Git and CI/CD.

Responsibilities

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.
Own how we measure whether the model answers the right clinical questions correctly and consistently; build evaluation, prompting and guard-rail approaches that keep output safe to show at the bedside.
Optimise inference performance on constrained on-device hardware, managing latency, memory and throughput within the CoMind One system.
Design and develop medical device software to IEC 62304 and ISO 14971, from real-time on-device behaviour through to the interfaces clinicians touch.
Ensure AI deployments meet cybersecurity requirements and regulatory standards, including FDA guidance for AI/ML-enabled devices.
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.

Skills

C++

Python

LLMs

Performance optimization

Git & CI/CD

On-device AI

Edge hardware

System integration

Regulatory awareness

AI safety

Tools

Jetson

Raspberry Pi

Job description

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.
Comfortable reasoning about performance: latency, memory and throughput on constrained hardware.
Strong with Git and CI/CD.

Nice to have

Edge / on-device AI: running models on constrained hardware such as Jetson, Android, iPad, Raspberry Pi or microcontrollers.
Hands-on with llama.cpp or similar, and evaluating small on-device models (e.g. Qwen, Gemma, MedGemma, custom).
Some hardware exposure: anyone doing genuine edge AI tends to have this.
Cloud experience (AWS), particularly running LLMs in a cloud environment.
A background in a regulated or safety-critical industry

Benefits:

Company equity plan so all employees share in the success of the company
Salary-sacrifice pension scheme
Private medical, dental and vision insurance (medical history disregarded)
Group life assurance at 4x annual income
Comprehensive mental health support, including unlimited access to 1:1 sessions with trained professionals
Unlimited holiday allowance (+ bank holidays) and one week of remote working per quarter
Lunch voucher (£10) every day for JustEat and free dinner on those days where you need to work later
Twice weekly deliveries of fresh fruit and an extensive selection of snacks and drinks
YuLife subscription, allowing you to turn your daily steps and meditation into discounts at a range of stores