Principal MLOps/GenAI Infrastructure Engineer

hackajob; London; Hybrid; GBP 76,000 - 88,000; Full time

Job summary

Join a leading technology firm as a Principal MLOps/GenAI Infrastructure Engineer, where you will lead the design and implementation of impactful machine learning platforms. Collaborate with various teams to redefine ML and AI technologies, empowering innovative solutions across the organization. The role offers a dynamic environment balancing office and remote work, contributing to the future of the BBC in a challenging and rewarding position.

Qualifications

• Extensive experience in cloud-native environments for ML/AI.
• Proven ability to drive technical initiatives.
• Strong understanding of the ML lifecycle.

Responsibilities

• Lead design and development of tooling for scalable MLOps workflows.
• Drive strategy for deploying large language models using AWS services.
• Support architectural decisions for scalable systems.

Skills

AWS services

DevOps

MLOps

Containerization

CI/CD

Security best practices

Collaboration

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Tools

Terraform

GitHub Actions

Jenkins

Docker

Kubernetes

Job description

Principal MLOps/GenAI Infrastructure Engineer

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Principal MLOps/GenAI Infrastructure Engineer

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hackajob is collaborating with BBC to connect them with exceptional tech professionals for this role.

Job Details

• Job Title: Principal MLOps Engineer
• Location: London / Salford / Glasgow / Newcastle / Cardiff (This is a hybrid role and the successful candidate will balance office working with home working)
• Band: D
• Salary: up to £76,700 - £87,600 (The expected salary range for this role reflects internal benchmarking and external market insights.)
• Closing Date for applications: Sunday 22nd June 2025 at 23:59
  
  

We’re happy to discuss flexible working. Please indicate your preference under the flexible working question in the application. There’s no obligation to raise this at the application stage, but if you wish to do so, you’re welcome to. Flexible working will be part of the discussion at offer stage.

Purpose Of The Role

Step into the world of the BBC, one of the UK's most iconic and beloved brands, where every working day is as unique as it is rewarding. Every tick of the clock, our content reaches millions of people globally, which is made possible by our top-notch Software Engineering team. They've been instrumental in pioneering innovative products and unique features that have firmly positioned us at the forefront of our industry. We don't merely adapt to an ever-changing world - we set the pace.

With this role you'll be at the heart of an exciting journey, crafting tools and patterns that are state-of-the-art and transformative. We are the catalysts, enabling the creation and collaboration of cutting-edge ML and AI technologies. Our work is pivotal in shaping the BBC's future, empowering teams across the organisation to explore, innovate, and redefine the landscape of media. Our team is building out new tools and capabilities to accelerate data science activities and the development of ML/GenAI applications. We enable teams across the BBC to build, collaborate on, manage, and maintain their machine learning platforms at scale.

You will play a key role in driving our ambition to build an outstanding software engineering team, environment, and culture. We are looking for a Principal Engineer to join our tech community to drive this transformation, build a modern digital ecosystem using exciting technologies and do the best work of their careers.

Your Key Responsibilities And Impact

• Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation.
• Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services.
• Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments.
• Design and support CI/CD pipelines using GitHub Actions, AWS CodePipeline, Jenkins, and other tools, with an emphasis on reliability, reusability, and performance.
• Contribute to the design and integration of monitoring and observability solutions (CloudWatch, Prometheus, Grafana) to ensure infrastructure and model health.
• Champion software engineering excellence through Test-Driven Development (TDD), rigorous test automation, and continuous quality assurance practices.
• Support architectural decisions for scalable and maintainable systems, collaborating with engineering and product stakeholders to align with business and technical goals.
• Partner with architects, product leaders, and stakeholders to shape the long-term technical vision and system architecture
• Apply and advocate for security best practices across the software development lifecycle using AWS-native tools and DevSecOps principles.
• Cultivate a high-performing engineering culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration.
  
  

Your Skills And Experience

• Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments.
• Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture.
• Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or Terraform in production environments.
• Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks.
• Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring.
• Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and GitOps workflows.
• Strong knowledge of advanced DevOps concepts, including progressive delivery strategies (blue/green, canary), resilience engineering, and performance optimisation.
• Deep understanding of cloud security, governance, and compliance, with the ability to define and implement scalable security frameworks.
• Proven ability to drive cross-functional technical initiatives, influence without authority, and deliver results through collaboration and alignment.
• In-dept understanding of the ML lifecycle, with practical experience deploying and managing LLMs and generative AI models in production.
  
  

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• Industry-recognised certifications such as AWS Certified DevOps Engineer, AWS Machine Learning Specialty, or AWS Solutions Architect - Professional.
• Strong written and verbal communication skills, with experience influencing technical direction across multiple teams or business units.
• Active contributor to open-source MLOps, GenAI, or DevOps projects and communities.
• Experience mentoring others, leading by example, and contributing to a culture of technical excellence.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Software Development

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