Location: UK-based hybrid role, occasional travel to site.
Day to day
* Design, build and deploy AI and machine learning solutions that deliver measurable customer and business value.
* Develop, train and optimise machine learning and generative AI models for use in production systems.
* Build and operate scalable data pipelines, model training workflows and inference services using cloud-native and managed AI platforms.
* Collaborate with product managers, engineers and data teams to translate business problems into effective AI solutions.
* Own the quality, performance and reliability of AI solutions, including monitoring, retraining and continuous improvement.
* Implement responsible AI practices, ensuring solutions meet security, privacy, governance and ethical standards.
* Evaluate and select appropriate AI tools, models and platforms, making build vs buy recommendations where appropriate.
* Support live AI services by investigating incidents, analysing model behaviour and resolving production issues.
* Continuously explore and apply new AI techniques, frameworks and approaches where they deliver clear benefit.
* Take ownership for delivering agreed outcomes, raising risks early and contributing to team delivery and learning.
What we need from you
* Degree in Computer Science, Data Science, Engineering or related discipline, or equivalent practical experience.
* Several years in software engineering with at least 2 to 3 years developing AI or machine learning solutions in production environments.
* Experience integrating AI models into enterprise platforms and customer-facing systems.
* Strong capability in machine learning frameworks, data modelling and API based integration.
* Ability to translate business problems into AI solutions, understanding of data governance, model evaluation and ethical considerations.
* Demonstrated experience working as an AI or machine learning engineer delivering models or AI services into production.
* Strong experience with modern machine learning and/or generative AI frameworks.
* Experience working with large language models, either through fine-tuning open source models or integrating with managed foundation model platforms.
* Hands‑on experience building data pipelines and model workflows using tools such as Python, SQL, Spark or similar data processing technologies.
* Experience deploying and operating AI systems in cloud environments using containerisation, managed ML services or serverless architectures.
* Understanding of MLOps practices including model versioning, experiment tracking, CI/CD for models and monitoring of model performance and drift.
* Experience applying responsible AI principles, including data privacy, bias mitigation, explainability and security controls.
* Ability to analyse complex problems, experiment iteratively and translate findings into robust engineering solutions.
* Strong collaboration and communication skills, with the ability to work effectively across engineering, product and data teams.
* A growth mindset with curiosity for emerging AI technologies and a focus on practical, value‑driven outcomes.
Core Competencies & Technical Skills
* Ability to design, integrate and operate AI enabled solutions within enterprise environments, including prompt-driven workflows, retrieval-augmented systems and AI agents, applying structured evaluation, testing and monitoring practices to ensure AI outputs are reliable, secure and compliant with organisational guardrails.
* Prepares and manages data used in AI workflows and takes responsibility for the responsible lifecycle of AI features from experimentation through to deployment and continuous improvement.
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