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- Tasks: Design and manage cloud infrastructure for AI services, optimising deployment pipelines.
- Company: Join a major UK government initiative transforming public services with AI.
- Benefits: Competitive salary, hybrid work, and the chance to shape future digital experiences.
- Why this job: Be at the forefront of AI innovation, making a real difference in citizens' lives.
- Qualifications: Experience in DevOps, cloud environments, and AI/ML workloads is essential.
- Other info: Exciting career growth opportunities in a dynamic, impactful environment.
The predicted salary is between 36000 - 60000 £ per year.
Clearance: Eligible for BPSS
Start: ASAP
Work pattern: Hybrid (London)
Work type: 12 month FTC (Competitive Salary)
We’re working with a major UK government initiative that’s shaping the future of how citizens interact with public services. The programme focuses on harnessing the latest AI technologies to deliver simpler, faster, and more efficient digital experiences across departments.
We’re looking for an experienced Cloud & DevOps Engineer to join the AI Customer Experience team - a multidisciplinary group driving innovation in Generative AI, conversational interfaces, and automation. You’ll design, build, and manage the infrastructure that powers large-scale AI services and agentic workflows across government systems.
Key Responsibilities- Design and provision secure, scalable cloud infrastructure (AWS, Azure, or GCP) using Python-based Infrastructure as Code (Terraform or Pulumi).
- Build and optimise CI/CD pipelines to automate the deployment of AI applications and models (MLOps / LLMOps).
- Containerise workloads using Docker and manage deployments through Kubernetes (KubeRay, Kubeflow, MLRun, or similar).
- Provision and manage the infrastructure required to run AI workloads, including vector databases and hyperscaler AI services.
- Develop automation scripts in Python to streamline operations and reduce manual tasks.
- Implement comprehensive monitoring, logging, and alerting to maintain high system reliability and performance.
- Provide technical support for complex issues and advise on modern engineering practices for large-scale projects.
- Strong background as a DevOps or Cloud Engineer in public cloud environments (AWS, Azure, or GCP).
- Experience deploying and managing infrastructure for AI/ML workloads using MLOps or LLMOps practices.
- Excellent scripting and automation skills in Python (e.g. Boto3, SDKs).
- Proven experience with Python-based IaC frameworks (Pulumi, Terraform, CDKs).
- Hands-on experience building CI/CD pipelines for AI deployments (Github Actions, MLFlow, ZenML, or similar).
- Deep understanding of containerisation and orchestration tools (Docker, Kubernetes).
- Experience deploying AI inference engines (vLLM, Ray Serve, Triton).
- Familiarity with observability tools for LLMs (TruLens, Helicone, LangSmith).
- Understanding of AI safety and reliability frameworks (Guardrails AI).
This is an exciting opportunity to help define the infrastructure powering the next generation of AI-driven public services. If you have the experience and passion to work on impactful projects within government, we’d love to hear from you.
DevOps Engineer (MLOps / LLMOps) employer: Amber Labs
Contact Detail:
Amber Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land DevOps Engineer (MLOps / LLMOps)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving MLOps or LLMOps. We want to see your work in action, so don’t be shy about sharing your GitHub or any relevant links.
✨Tip Number 3
Prepare for interviews by brushing up on common DevOps questions and scenarios. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace DevOps Engineer (MLOps / LLMOps)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of a DevOps Engineer. Highlight your experience with cloud environments and MLOps practices, as well as any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and public services. Share specific examples of your work in DevOps and how you can contribute to our mission at StudySmarter. Keep it engaging and personal!
Showcase Your Technical Skills: Don’t forget to showcase your technical skills in your application. Mention your experience with Python, Terraform, Docker, and Kubernetes. We love seeing candidates who can demonstrate their hands-on experience with these tools!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining the StudySmarter team!
How to prepare for a job interview at Amber Labs
✨Know Your Tech Stack
Make sure you’re well-versed in the specific technologies mentioned in the job description, like AWS, Azure, or GCP. Brush up on your Python scripting and Infrastructure as Code tools like Terraform or Pulumi, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss your previous projects that involved MLOps or LLMOps. Be ready to explain how you designed and managed cloud infrastructure, built CI/CD pipelines, and containerised workloads. Real-world examples will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Bigger Picture
Familiarise yourself with the government initiative and its goals. Understanding how your role as a DevOps Engineer fits into the larger mission of improving public services through AI will show your enthusiasm and commitment to the project.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the challenges they face, and the technologies they use. This not only shows your interest but also helps you gauge if the company culture aligns with your values and work style.
