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Delivery Lead
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Data Science & AI Delivery Lead
London
Hybrid – minimum 3 days per week in the local office
£90,000–£120,000 base + 15–20% target bonus
We are looking for an experienced Data Science & AI Delivery Lead to join a major international organisation investing significantly in Data, AI and advanced analytics.
This is a senior, hands-on technical leadership position for someone who can combine AI/ML engineering expertise with delivery leadership. You’ll act as the deputy to the Head of Data Science & AI Delivery, taking responsibility for the day-to-day execution of AI initiatives and helping a growing team take solutions from concept and proof of value through to scalable production deployments.
The organisation sees Data and AI as a major strategic capability – using information to make better decisions, identify opportunities earlier, improve operational efficiency and create competitive advantage.
Importantly, this is not a purely managerial role. You’ll remain close to the technology, working directly with the codebase, reviewing technical designs and architecture, establishing engineering standards and contributing hands-on when required.
You’ll take a leading role in the technical execution and delivery of AI, machine learning and advanced analytics solutions, including:
- Owning the day-to-day running of AI delivery workstreams, ensuring teams remain focused, unblocked and aligned to priorities.
- Acting as deputy to the Head of Data Science & AI Delivery and providing leadership continuity across projects and stakeholder forums.
- Taking technical delivery accountability from initial concept through development, deployment and production.
- Leading AI solution architecture, technical design reviews, implementation approaches and production-readiness assessments.
- Establishing engineering standards, reusable frameworks, patterns and best practices for AI delivery.
- Providing technical guidance around solution design, model selection and architecture.
- Remaining hands-on with Python development, particularly during critical delivery phases and proof-of-concept work.
- Reviewing code and technical outputs to maintain high engineering and quality standards.
- Designing and delivering Generative AI and LLM solutions, including RAG architectures, prompt engineering, vector search and integration with Azure AI services.
- Defining engineering approaches for LLM applications, agentic AI systems, machine learning solutions and AI platforms.
- Establishing strong MLOps practices covering model versioning, automated testing, deployment pipelines, monitoring, observability and model lifecycle management.
- Ensuring solutions meet appropriate security, governance, scalability, explainability and operational support requirements.
- Evaluating emerging AI technologies and determining where they can deliver meaningful business value.
- Working closely with architecture, technology, programme and Data Engineering teams to ensure effective end-to-end delivery.
- Supporting delivery planning, timelines, cost estimates, cloud/API consumption and resource allocation.
- Mentoring Data Scientists and AI Engineers through architecture reviews, code reviews, pair programming and technical coaching.
- Helping create a high-performing engineering culture focused on collaboration, quality and continuous learning.
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You’ll need demonstrable experience delivering AI and machine learning solutions into production within a professional environment, alongside the technical credibility to lead experienced Data Scientists and AI Engineers.
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Key experience includes:
- Expert-level Python development.
- Strong experience with core data science and machine learning libraries such as scikit-learn, pandas, PyTorch and/or TensorFlow.
- Practical experience with Databricks, including MLflow and Spark-based data processing.
- Hands-on knowledge of Generative AI and LLMs, including prompt engineering, RAG architectures and vector search.
- Strong understanding of MLOps, including CI/CD, model testing, deployment, monitoring and model lifecycle management.
- Cloud experience, ideally within the Microsoft Azure ecosystem.
- Experience with services such as Azure OpenAI, Azure Machine Learning and/or Azure AI Search.
- Experience leading technical delivery teams while remaining actively involved in engineering and delivery.
- Strong understanding of software engineering practices including Git, code review, documentation and the transition from experimentation to production-grade code.
- Excellent stakeholder communication skills, including the ability to translate complex technical concepts into clear business language.
- Strong delivery and project management capabilities, including resource estimation, progress tracking and managing competing priorities.
We’re particularly interested in people who combine technical depth with leadership ability – someone comfortable discussing strategy with senior stakeholders one moment and reviewing Python code or AI architecture with engineers the next.
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