AI Engineer

Location: London, UK Wide (50% Remote)
Inside / Outside IR35: Inside IR35
Duration: 6 Month Contract

A bit about the job

We are looking for an experienced AI Engineer to design, build, deploy and operate AI solutions that deliver measurable business value across Aviva.

This is a hands-on engineering role where you’ll own the end-to-end AI lifecycle — from understanding and framing a business problem, through solution design and development, to production deployment, monitoring and continuous improvement.

You’ll work across both traditional machine learning and generative AI, making informed decisions about the right approach for each use case. This could include developing ML models, building LLM-powered features, designing retrieval and prompt pipelines, or combining different AI approaches to deliver the best outcome.

Working as part of a multidisciplinary product or AI team, you’ll collaborate closely with software engineers, data engineers and product stakeholders to bring AI solutions into production. You’ll also play an important role in ensuring solutions are reliable, cost-effective and responsibly engineered within a regulated financial services environment.

Skills and experience we're looking for

• Proven commercial experience as an AI Engineer, Machine Learning Engineer, ML Engineer, Software Engineer or similar.
• Strong AI engineering capability across traditional machine learning and generative AI.
• Demonstrable experience taking AI or ML solutions from development through to production.
• Strong Python and software engineering skills, with experience writing production-quality code.
• Practical experience with model development, training, evaluation, deployment and monitoring.
• Experience designing and implementing feature engineering, training and evaluation pipelines.
• Experience working with LLM-powered applications, including prompt engineering, retrieval strategies or similar GenAI techniques.
• Ability to assess a business problem and select the most appropriate approach, whether traditional ML, generative AI or a combination of both.
• Experience working with cloud-based AI platforms and associated services.
• Working knowledge of MLOps and/or LLMOps practices and tooling.
• Experience monitoring live AI/ML systems, diagnosing issues and using production performance data to drive improvements.
• Understanding of model evaluation and how to establish appropriate measures for quality, performance, safety and production readiness.
• Experience applying responsible AI practices, including bias and fairness testing, output evaluation, guardrails and data protection.
• Understanding of the challenges involved in deploying AI within a regulated environment.
• Ability to identify technical, model and governance risks and escalate material concerns appropriately.
• Experience collaborating with software engineers, data engineers, product teams and business stakeholders.
• Strong documentation skills, including producing technical and governance artefacts required for audit, assurance and knowledge continuity.
• Comfortable participating in design discussions, architecture reviews, code reviews and engineering forums.
• Strong analytical and problem-solving skills, with the ability to validate data assumptions and assess model behaviour.
• Ability to communicate technical decisions clearly to both technical and non-technical stakeholders.
• Degree in Computer Science, Engineering, Mathematics or a related discipline, or equivalent professional experience.
• Relevant cloud or AI certifications would be advantageous.
• Demonstrable experience delivering AI solutions into production environments.