Principal Software Engineer - GenAI

This job is with BBC, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Job Details

Job Title:

Principal Software Engineer - GenAI
Salary: £80,000 - £90,000 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights
Band: D

Location:

London / Salford / Glasgow /  Newcastle / Cardiff (Candidates will be considered for either location. This is a hybrid role and the successful candidate will balance office working with home working)
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 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 Sage Maker, Bedrock, and related services.
Guide the adoption of Infrastructure as Code practices using AWS CDK and Cloud Formation 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 Git Hub Actions, AWS Code Pipeline, 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 Cloud Watch, 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 Dev Sec Ops  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 Dev Ops 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 Sage Maker, 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, Cloud Formation, or Terraform in production settings.
Proven success designing and ope rationalising complete MLOps pipelines using tools such as MLflow, Sage Maker 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 Git Hub Actions, Jenkins, and Git Ops workflows, complemented by strong knowledge of advanced Dev Ops concepts such as progressive delivery…