BBC Career Opportunities Lead AI Engineer

JOB BAND: E
CONTRACT TYPE: Permanent Full-time
DEPARTMENT: BBC Media Technology
LOCATION: Salford
PROPOSED SALARY RANGE: 80000 - 90000 depending on relevant skills knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.

The Lead AI Engineer (Gen AI) will help the BBC make practical use of AI tools and systems to solve business problems and help our internal teams work effectively and efficiently.

The role will collaborate closely with project managers data scientists analysts domain experts and the BBCs technical teams to build the data pipelines and technical solutions that enable AI projects to move effectively through piloting to successful handover to the business for scaling.

WHY JOIN THE TEAM

These roles will sit within BBC Media Technology and be embedded within the BBCs Strategy and Transformation team focusing on Gen AI transformation.

The Generative AI Team helps the BBC realise value from rapidly evolving AI capabilities in a way that is practical responsible and aligned to the BBCs public service mission. The teams activities include enabling adoption of AI tools across the organisation; leading innovation and transformation work; and leading the BBCs engagement on the wider AI issues that shape our operating environment.

The work we do makes the most of AI to deliver value for the BBCs teams and audiences. The challenges are new and exciting and youll have real influence over how one of the worlds most trusted public broadcasters adopts AI in a way that is practical responsible and true to its values.

YOUR KEY RESPONSIBILITIES AND IMPACT

• Develop secure reliable and well-designed solutions that support high-quality AI piloting and transition to successful handover to the business for scaling.
• Design and build robust data pipelines models and supporting data structures that enable AI projects to move effectively from piloting to successful handover into the business for scaling.
• Work closely with data scientists analysts project managers business partners researchers and designers to understand requirements and translate them into valuable solutions.
• Establish and promote strong engineering practices for data quality resilience maintainability and operational performance across the teams work.
• Help shape data approaches to architecture integration and pilot design ensuring solutions are appropriate for AI experimentation and future scaling.
• Provide technical leadership to other engineers mentoring code review and setting standards contributing to a culture of learning and continuous improvement.
• Ensure data used within AI projects is managed in line with the BBCs organisational values security requirements and responsible approach to AI.

Essential criteria

• Significant experience of designing and delivering LLM-based workflows or applications including pipelines models and platform components with the engineering discipline to build secure resilient and maintainable systems in complex organisational environments.
• Strong engineering practices including proficiency in Python and demonstrable use of AIassisted development tools to improve code quality and delivery pace.
• Significant hands-on experience with:
  • cloud platforms and infrastructure (AWS preferred) including Infrastructure as Code;
  • container and orchestration tools (e.g. Docker Kubernetes)
  • API development frameworks (FastAPI or equivalent);
  • Experience of working collaboratively in multidisciplinary teams translating a range of user product and research needs into practical engineering solutions.
• Demonstrable experience of providing technical leadership to other engineers mentoring reviewing code setting standards and improving engineering practices.

Desirable criteria

• Good understanding of data governance security and quality considerations with the judgement to apply these appropriately in innovative or experimental contexts.
• Experience working in broadcast media start-up or research environments.
• Contributions to published technical documents or thought leadership in your area of expertise.
• Experience building with Generative AI frameworks (e.g. LangChain LangGraph PydanticAI) and managed AI services (e.g. Bedrock Azure).