BBC Career Opportunities Senior AI Engineer

JOB BAND: D
CONTRACT TYPE: Permanent Full-time
DEPARTMENT: BBC Media Technology
LOCATION: Salford
PROPOSED SALARY RANGE: 60000 - 70000 depending on relevant skills knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.

The Senior 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

• Help evaluate AI and automation capabilities both existing and emerging using data and
  evidence to inform decisions about the most appropriate solutions for BBC contexts.
• Design and develop data pipelines technical components and supporting capabilities that
  enable the evaluation and adoption of agentic and AI automation tooling.
• Work with colleagues across the team to design AI agentic and automation solutions that
  address clearly defined operational or domain-specific problems.
• Build secure resilient and maintainable data engineering solutions that support
  experimentation as well as more scalable use where appropriate.
• Collaborate closely with domain experts data scientists analysts researchers designers and
  project management teams to translate requirements into valuable solutions.
• Contribute to good engineering practice across the team supporting high standards in data
  quality governance documentation and continuous improvement.
• Ensure work is carried out in line with the BBCs organisational values security requirements
  and responsible approach to AI adoption.

Essential criteria

• Experience with designing delivering LLM-based workflows or applications including
  pipelines models and platform components.
• Strong engineering practices including proficiency in Python and demonstrable use of AI
  assisted development tools to improve code quality and delivery pace.
• Hands-on experience with:
  • Cloud platforms and infrastructure (AWS preferred) including Infrastructure as Code
  • Container and orchestration tools (e.g. Docker Kubernetes)
• Experience of working with multidisciplinary teams to understand business or user problems
  and translate them into valuable solutions.
• Ability to evaluate new tools or technologies critically using evidence and sound judgement
  to assess their effectiveness and suitability.

Desirable criteria

• Familiarity with API development frameworks (FastAPI or equivalent).
• Experience building with Generative AI and agentic frameworks (e.g. LangChain LangGraph
  PydanticAI) and managed AI services (e.g. Bedrock Azure).
• Familiarity with enterprise automation toolsets (e.g. Microsoft Power Platform Copilot
  Studio) and an understanding of how they complement bespoke AI solutions in large
  organisations.
• Sound understanding of data governance security and quality considerations with the
  ability to apply these appropriately in innovative or experimental contexts.
• A strong academic background or research credentials in data or AI engineering or a related
  discipline.