Principal Software Engineer - GenAI

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 tooling and platforms that enable scalable Data Science, MLOps, and LLMOps workflows, while driving strategy for deploying, serving, and monitoring large language models in real time and batch environments using Amazon SageMaker, Bedrock, and related services.
• Guide the adoption of Infrastructure as Code practices using AWS CDK and CloudFormation to build secure, maintainable cloud environments, while supporting architectural decisions that ensure systems are scalable, resilient, and aligned with business and technical goals.
• Design and support reliable and reusable CI and CD pipelines using GitHub Actions, AWS CodePipeline, Jenkins, and other tools, while championing software engineering excellence through Test Driven Development, rigorous automated testing, and continuous quality assurance.
• Contribute to the integration of monitoring and observability solutions such as CloudWatch, Prometheus, and Grafana to maintain both model health and platform stability, while applying and advocating for security best practices across the software development lifecycle using AWS native tools and DevSecOps principles.
• Partner closely with architects, engineering teams, and product stakeholders to shape long term technical strategy, while cultivating a high performing engineering culture through mentorship, knowledge sharing, internal technical sessions, and cross team collaboration.

Your Skills And Experience

• Extensive experience in DevOps and MLOps roles with a strong record of building, scaling, and securing ML and AI infrastructure in cloud native environments, supported by deep understanding of the ML lifecycle and practical experience deploying and managing LLMs and generative AI models in production.
• Strong expertise across AWS services including SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, and ECS or EKS, combined with solid cloud solution architecture skills and advanced proficiency in Infrastructure as Code using AWS CDK, CloudFormation, or Terraform in production settings.
• Proven success designing and operationalising complete MLOps pipelines using tools such as MLflow, SageMaker Pipelines, or similar frameworks, alongside extensive experience building and operating containerised applications with Docker and Kubernetes in production environments.
• Deep hands on capability with CI or CD best practices, including GitHub Actions, Jenkins, and GitOps workflows, complemented by strong knowledge of advanced DevOps concepts such as progressive delivery strategies including blue green and canary releases, resilience engineering, and performance optimisation.
• Strong background in cloud security, governance, and compliance with experience defining and implementing scalable security frameworks, together with a proven ability to drive cross functional technical initiatives, influence without authority, and deliver results through collaboration and alignment.

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 GenAI Developer, ML Engineer, 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.

Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Contracts of Employment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer.