About us

Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster.

We’re looking for talented people who want their work to matter. With offices in Cambridge and London, you’ll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials.

The DevOps team operates an infrastructure imaging platform on multiple clouds that supports a SaaS product used by our global customers to run clinical trials. Qureight’s imaging platform is validated software operating under GxP, 21 CFR Part 11 and ISO/IEC 27001 requirements. The underlying infrastructure must therefore be secure, reproducible and fully auditable, without compromising performance. We also maintain machine learning experiment and development infrastructure for our Science team.

About the role  

As a DevOps Engineer, you will maintain and build on this infrastructure, working with the Platform, Data Engineering and Science teams to deploy and monitor our production, development and research environments.

You’ll work with AWS, Kubernetes, infrastructure as code and GitOps, supporting both the production SaaS product and the machine learning environments where our scientists train and develop models.

You’ll join a small, hands-on team led by our Head of DevOps, where you’ll have real ownership of the systems you work on. The overall goal is to keep improving our practices and processes for deployment, security and reliability at scale, while meeting the change control and documentation standards expected of a regulated software platform.

We will also consider part-time applications for this role (minimum 0.8 FTE).

What you will do  

Build and maintain our cloud infrastructure as code using IaC tooling

Operate, upgrade and monitor our Kubernetes clusters across production, development and research environments

Run GitOps-based deployments of our software and support release management for a validated platform with strict, versioned release cycles

Build, maintain and improve CI/CD pipelines in GitLab

Develop monitoring, logging and alerting, and take part in incident response and root cause analysis

Carry out routine security maintenance and implement best practice, including patching, vulnerability remediation, secrets management and least-privilege access

Monitor, report on and optimise cloud costs

Support internal teams with solutions for their deployment and infrastructure requirements, including ML training and model deployment infrastructure

Write and maintain technical documentation, runbooks and change records that support our GxP, 21 CFR Part 11 and ISO/IEC 27001 obligations

Requirements

What we need  

2+ years of industry experience in applied DevOps, platform or site reliability engineering

Strong proficiency with Linux operating systems

Hands-on experience with a major cloud provider (AWS preferred), including cost monitoring and management

Experience working with Kubernetes in a live production environment

Experience of GitOps working methods and deployment strategies in a live production environment

Experience with infrastructure as code tooling at scale (Terraform or OpenTofu preferred)

Experience building and maintaining CI/CD pipelines

Experience with monitoring and logging frameworks such as CloudWatch, CloudTrail, Prometheus and Grafana

Ability to use scripting languages such as Bash for complex operations, and to read and understand Python code

Strong written and verbal communication skills, including writing clear technical documentation

Even better if you have…

Experience with machine learning model management, e.g. model registries, packaging and deployment

Experience with machine learning training infrastructure and experiment logging (MLflow preferred)

Experience working with validated software platforms with strict versioned release cycles, or in other regulated environments e.g. GxP, 21 CFR Part 11, ISO/IEC 27001

Experience producing maintainable, testable, documented, production-grade code

Experience with container and cloud security tooling, e.g. image scanning, policy as code or secrets management

Exposure to medical imaging (e.g. DICOM) or other healthcare data

Relevant certifications, e.g. AWS Certified DevOps Engineer or Certified Kubernetes Administrator (CKA)

Benefits

What can you expect from us 

A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, cycle-to-work scheme, and a contributory pension scheme  
Equity, so that our team can share in the long-term success of Qureight
28 days’ holiday allowance, 25 days’ annual leave and 3 additional company days between Christmas and New Year, plus bank holidays and enhanced family leave
A diverse work environment that brings together experts in many fields, including software engineering, DevOps, data science, machine learning, quality assurance, regulatory affairs, and clinical operations.

How to apply 

Please upload a CV and covering letter by clicking 'Apply Now'. Your covering letter should explain why you are applying for the job and what skills and experience you can bring to the role.  

We review CVs as we receive them and interview as soon as we have applications that look like a good match (usually within one week). We do not use closing dates. So, please apply as soon as possible to avoid missing out on this role. We advertised this role on 29th October. 

If you have any queries, please contact careers@qureight.com.

Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity. 

Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply – you may be a great fit, even if you don’t meet every qualification. We’d love to hear from you. 

If you require any adjustments to the application or selection process, please let us know. We will be happy to support you. 

DevOps Engineer

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