MLOps Engineer

MLOps Engineer

About the Job

In a Nutshell

💻 Role:

MLOps Engineer

📄 Employment Type:

Permanent

📍 Location:

UK remote/hybrid

🔒 Clearance:

Eligible for SC Clearance (BPSS start possible while SC is sponsored)

About Amber Labs

The digital transformation partner for highly regulated industries.

Our teams deliver digital transformation for organisations operating in complex, highly regulated environments. From securing national borders to supporting critical defence operations, we deliver secure AI, data, cloud and software solutions across high-stakes programmes.

What You’ll Be Doing

We’re looking for experienced MLOps Engineers to join Amber Labs on an exciting AI programme supporting a leading UK defence and technology organisation.

The organisation has already invested in building an enterprise AI platform on Microsoft Azure, including its security foundations, data pipelines and core AI capabilities. The next challenge is turning that investment into real, production-ready AI solutions that deliver measurable business value.

You’ll play a key role in making that happen, building and operating the deployment pipelines, infrastructure, monitoring and automation needed to run AI and machine learning workloads securely and reliably in an enterprise environment.

Working alongside AI Engineers, Cloud and Solution Architects, and technical leadership, you’ll help deliver the programme’s first production AI use case while establishing reusable engineering practices that can be adopted across future workloads.

This is an opportunity to work on the practical side of AI delivery, moving beyond proofs of concept and helping build the foundations for AI capabilities that work reliably in the real world.

You’ll be responsible for:

• Building and maintaining CI/CD pipelines for AI and machine learning workloads within an existing Azure environment.

• Automating the deployment, configuration and release of AI services, models and supporting components across environments.

• Implementing infrastructure as code using Terraform, working within the existing platform and Control Plane rather than creating parallel infrastructure.

• Supporting the containerisation, deployment and operation of AI workloads, ensuring they can run reliably and securely in production.

• Developing and maintaining automated processes for model deployment, version control, testing and release management.

• Implementing monitoring, logging and observability for production AI workloads, integrating with existing Azure monitoring and Log Analytics capabilities.

• Supporting operational reliability through troubleshooting, performance monitoring, incident investigation and continuous improvement.

• Working with AI Engineers to productionise model integrations, inference services and retrieval-augmented generation (RAG) capabilities.

• Applying security, governance and compliance requirements throughout the AI delivery lifecycle.

• Managing dependencies and approved software packages in line with enterprise controls and existing platform tooling.

• Working with GitLab, Terraform and associated tooling to deliver repeatable, auditable infrastructure and deployment processes.

• Collaborating with architecture and engineering colleagues to ensure solutions integrate with existing security, data and platform services.

• Establishing reusable deployment patterns, automation and operational practices that can support additional AI use cases as the programme scales.

• Contributing to the longer-term evolution of the platform, including its future extension into on-premises environments where required.

What We’re Looking For

You will need:

• At least five years’ experience in platform engineering, DevOps or MLOps, with practical experience supporting production workloads.

• Strong experience building and maintaining CI/CD pipelines, ideally using GitLab CI/CD or similar tooling.

• Hands-on experience with infrastructure as code, particularly Terraform.

• Experience deploying and operating containerised applications and services.

• A solid understanding of cloud infrastructure, ideally within Microsoft Azure.

• Experience implementing production monitoring, logging and observability, with the ability to troubleshoot issues across deployed services.

• Practical experience supporting the deployment and operational management of machine learning models or AI workloads.

• An understanding of the machine learning lifecycle, including model versioning, deployment, testing, monitoring and ongoing maintenance.

• Experience working in security-conscious enterprise environments where access controls, auditability and approved dependencies are important.

• The ability to work effectively with data scientists, AI Engineers, architects and other technical stakeholders to move solutions into production.

• A pragmatic, hands-on approach to engineering, with a focus on building reliable solutions rather than stopping at prototypes.

• Eligibility to undergo SC security clearance, with the potential to start on BPSS while SC clearance is sponsored.

It would be particularly useful if you also have:

• Experience with Azure Machine Learning, Azure OpenAI or other Azure-native AI services.

• Familiarity with MLOps tooling and practices for automating model training, deployment and monitoring.

• Experience working with Docker, Kubernetes or similar container orchestration technologies.

• Knowledge of enterprise data platforms, data lakes and the integration of AI services with governed data environments.

• Familiarity with Azure Monitor, Log Analytics, Microsoft Sentinel or similar monitoring and security tooling.

• Experience managing software dependencies and artefacts through tools such as Nexus.

• Experience working within defence, government or other highly regulated industries.

If this role sounds like a good fit but you don’t tick every box, don’t let that stop you. We’d still love to hear from you.

What’s In It For You

We believe benefits should be practical: things that genuinely support your day-to-day, give you flexibility and help you keep developing.

Here are a few of our perks:

• 25 days’ annual leave, plus bank holidays

• Private medical insurance with Bupa

• Remote-first working, with access to our Liverpool Street office

• Personal training budget to support your professional development

• Perkbox membership, with discounts across retail, travel, dining and wellness

• Electric Vehicle Scheme after one year of service

• Regular team socials

• Referral scheme offering up to £3,000 for successful hires

• Employer pension contributions

• Your choice of PC or Mac

How We Work

We’ve worked hard to build a team of people who are experts at what they do. Because of that, we’ll trust you to get on with your job and give you the space to do it well. But you’ll always have plenty of support around you whenever you need it, whether that’s to sense-check an approach, tackle a tricky client challenge, or simply bounce ideas around.

We keep our structure flat and our processes straightforward. If you have a good idea, you’ll be encouraged to run with it, and if something could be done better, we’ll encourage you to say so. Ultimately, we work with people who take pride in their work, support their team and want to leave things better than they found them.

Learn more about how we work.

What Happens Next?

Once you’ve applied, our in-house Talent team will review your application and, if it looks like there could be a good fit, they’ll be in touch.

For most of our roles, there are two interview stages: one focused on your technical expertise, and another focused on how you communicate and approach your work. We’re big believers that both are equally important!

For some roles, there may also be a final conversation with one of our Senior Leadership Team.

Get to know them and the rest of our SLT here.

A Human Approach to Hiring

We use AI responsibly, in our client projects and internally. When it comes to hiring, though, there are always real people behind the process. Decisions throughout, from CV review and progressing to interview through to making an offer, are made by our Talent team (who are real people, we promise!).

Diversity & Inclusion

Amber Labs is an equal opportunities employer, and we’re committed to creating an inclusive environment where everyone has the opportunity to do their best work, regardless of background, identity or experience.

If there’s anything we can do to make the recruitment process more accessible or comfortable for you, just let our Talent team know. We’ll be happy to help!