NHS Business Services Authority
Senior AI (Artificial Intelligence)/ML (Machine Learning) Engineer
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Senior AI (Artificial Intelligence)/ML (Machine Learning) Engineer
Job Summary
The NHS Business Services Authority is looking for a Senior AI/ML Engineer to help design, build, and scale Artificial Intelligence and Machine Learning solutions that deliver real-world impact across the organisation.
The NHSBSA manages over £100 billion of NHS spend annually and delivers services supporting NHS organisations, healthcare professionals, patients, and the public. Data and AI are central to the organisation's ambition to become truly data driven, creating opportunities to improve outcomes and drive innovation across health and care.
You'll work with a dedicated team in an organisation that genuinely invests in its people recognised in the 2025 Global Top 100 Most Inspiring Employers, a 2025 UK Inspiring Workplaces finalist, and named by Best Companies as one of the UK's best places to work.
Please note this vacancy may close early if a high volume of applications is received, so early application is encouraged.
What do we offer?
- Hybrid working - offering flexibility to work predominantly from home with the opportunity to be office based should you prefer, or if business needs require it.
- 27 days leave (increasing with length of service) plus 8 bank holidays.
- Opportunities for development
- Active wellbeing and inclusion networks
- Excellent pension
- Various salary sacrifice schemes
- Employee Assistance programme, offering free 24/7 support for you and your loved ones
- Access to a wide range of benefits and high street and online discounts.
Main duties of the job
As Senior AI/ML Engineer, you will be responsible for leading the technical development and deployment of AI solutions that drive innovation, improve services, and support evidence-based decision-making. You will work across cross-functional teams to design, train, deploy and scale models for use in products and services, applying responsible AI principles.
You'll own and enhance the AI/ML tooling ecosystem including experiment tracking, data pipelines, data access, model deployment pipelines, CI/CD for ML, and ensure deployed models are continuously monitored using observability tools to detect performance degradation, data drift, and operational issues.
You'll rapidly experiment with emerging AI tools and models (including generative AI and ML-driven automation) to solve business problems, evaluating and integrating effective solutions to continuously improve services. Collaborate across cross-functional teams using agile practices and feedback loops to deliver user-centred AI solutions that are scalable, inclusive, accessible, and aligned with public sector outcomes.
About Us
Here at the NHS Business Services Authority (NHSBSA), what we do matters.
- We manage the NHS Pension scheme, process prescription payments and much more. Our services are used by NHS organisations, contractors and the public: we're proud to be part of something meaningful, that touches millions of lives.
- We design our services around customer needs and place people at the heart of our organisation. That's why when you join us, you'll be empowered and supported to help your career grow.
- As one of the UK's Best Big Companies to work for, we're connected to our values: Collaborative, Adventurous, Reliable and Energetic. We care about our people, our purpose, and your progress.
- We strive to offer a fantastic colleague experience, where every colleague is heard, supported and respected. Wellbeing, diversity and inclusion is at the centre of this, and you can join our Lived Experience Networks who help us bring our authentic selves to work.
- We're committed to being a flexible employer and we try to offer a working pattern that suits you where possible, through hybrid working, flexible hours and more.
- Alongside a competitive salary with pay progression, we offer a people-centric benefits package, connecting you to the rewards and benefits you value most!
- Ready to join us in delivering business service excellence to the NHS, helping people live longer, healthier lives? Apply today and see where the NHSBSA can take you.
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Job Description
Job responsibilities
In this role, you are accountable for:
AI Engineering and development
- Designing, developing, and deploying AI solutions from prototype to production, ensuring scalability, security, and maintainability.
- Collaborate on feature engineering, data preprocessing and documentation using industry standards (e.g., model cards, data sheets) to improve model accuracy and transparency.
- Contributing to shared libraries and frameworks that support model training, evaluation, and deployment.
- Applying SOLID principles, design patterns, and dependency injection to AI systems, ensuring maintainability and robustness.
- Owning and enhancing the AI/ML tooling ecosystem including experiment tracking, data pipelines, data access, model deployment pipelines, CI/CD for ML, and ensure deployed models are continuously monitored using observability tools to detect performance degradation, data drift, and operational issues.
- Conducting technical design reviews and implement robust testing and validation of both code and AI/ML models, ensuring quality, reproducibility, performance and adherence to groups and industry best practices.
- Applying secure coding practices and contributes to risk assessments for AI systems, including data privacy, model robustness, and adversarial threats.
- Rapidly experimenting with new AI tools and models (for example, building generative AI agents or other ML-driven automation) to solve business problems. You'll evaluate emerging technologies and integrate the best solutions quickly to continuously improve our services.
AI governance, ethics and security
- Ensuring responsible and complaint AI development with ethical, privacy and regulatory frameworks and standards
- Applying bias detection and mitigation techniques to promote fairness and inclusivity in AI models.
- Ensuring model decisions are explainable and auditable using industry-standard tools and techniques (e.g., SHAP, LIME).
- Supporting evaluation of third-party AI tools and vendors, ensuring alignment with ethical, technical, and procurement standards.
Collaboration and communication
- Collaborating across cross-functional teams (including data scientists, data engineers, analysts, service designers and other engineers) using agile practices and feedback loops to deliver user-centred AI solutions that are scalable, inclusive, accessible and aligned with public sector outcomes.
- Listening to and interpreting the needs of technical and non-technical stakeholders, and managing their expectations
- Producing well-written and technically sound reports and providing constructive review and assurance of reports authored by others.
- Educate stakeholders on AI system capabilities, limitations, and ethical considerations.
Continuous learning and innovation
- Evaluate models and systems for cost efficiency, performance and scalability against standard benchmarks.
- Stay ahead of developments in GenAI (e.g., LLMs, multimodal models), ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), orchestration tools (e.g., LangChain, LangFuse), model hubs. Taking responsibility for your own continuous professional development.
- Fostering a culture of responsible innovation and continuous learning.
- Supporting the development of talent within the team by delivering specialist training and providing ongoing coaching and mentoring, including promoting best practices in coding, model development, and MLOps (e.g., code review standards, model evaluation and monitoring, data ethics).
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Finance and Change
- Contribute to continuous business plans including budget monitoring
- Contribute to and prepare proposals for change including producing necessary estimates, mandates, and business cases within the relevant departments
In addition to the above accountabilities, as post holder you are expected to:
- Undertake additional duties and responsibilities in line with the purpose of your role and as agreed by your line manager.
- Demonstrate NHSBSA values and core capabilities in all aspects of your work.
- Encourage an environment where your own and colleagues safety and well-being is promoted.
- Contribute to a culture which values diversity and inclusion.
- Follow NHSBSA policies, procedures, and protocols as they apply to your role.
Working relationships
Responsible to: DDaT People Manager and AI Lead
Key relationships and connections:
- AI Lead
- Data Colleagues
- AI Team
Person Specification
Skills
Personal Qualities, Knowledge and Skills Essential
- A strategic thinker with a delivery mindset--able to scope, prioritise and drive AI initiatives effectively
- Strong intellectual curiosity and an inquisitive approach to emerging technologies and strategic challenges.
- Positive, proactive approach to teamwork and problem-solving.
- Personally motivated, proactive and resilient in navigating ambiguity and complexity.
- Committed to continuous professional development in AI and emerging technologies.
- Promotes best practices in coding, model development, and MLOps.
- Shares expertise and mentors colleagues and engineers.
- Excellent understanding of model lifecycle, from experimentation to production.
- Strong grasp of software engineering principles (SOLID, design patterns), dependency injection, and scalable system design.
- Strong understanding of NLP, embeddings, and semantic search.
- Awareness of ethical and privacy implications of AI including bias, fairness, and transparency.
- Awareness of ISO/IEC 42001:2023 - Artificial Intelligence Management System (AIMS).
- Strong understanding of statutory legislation relevant to AI, including freedom of information, data protection and equalities.
- Knowledge of cloud platforms used for AI (e.g., AWS, Azure) and MLOps tools (e.g., MLflow, Docker).
- Understanding of data pipelines, feature engineering, and data quality considerations in ML workflows.
- Familiarity with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
- Understanding of system design and secure deployment practices.
- Strong software engineering and machine learning skills. This includes proficiency in Python and other languages (e.g., Typescript, Go, C#, Rust, etc).
- Proficiency in at least one programming language (e.g., Python, Scala, etc) plus SQL.
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