Senior AI Engineer

At Kainos, we’re problem solvers, innovators, and collaborators - driven by a shared mission to create real impact. Whether we’re transforming digital services for millions, delivering cutting-edge Workday solutions, or pushing the boundaries of technology, we do it together.

We believe in a people-first culture , where your ideas are valued, your growth is supported, and your contributions truly make a difference. Here, you’ll be part of a diverse, ambitious team that celebrates creativity and collaboration.

Ready to make your mark? Join us and be part of something bigger.

MAIN PURPOSE OF THE ROLE & RESPONSIBILITIES IN THE BUSINESS: As a Senior Artificial Intelligence (AI) Engineer (Senior Associate) in Kainos, you’ll be responsible for developing high quality solutions that use AI and ML technologies which delight our customers and impact the lives of users worldwide. It’s a fast-paced environment so it is important for you to make sound, reasoned decisions. You’ll do this whilst learning about new technologies and approaches, with talented colleagues that will help you to learn, develop and grow as you, in turn, mentor those around you. MINIMUM (ESSENTIAL) REQUIREMENTS: • Proficient in designing, building, testing and maintaining production software applications that integrate AI services and include data science models. • Proficient applying mathematics principles to gain insight from data. • Experience of applying development patterns in relation to security, scalability and performance. • Contributing to technical decisions and direction in a collaborative team environment, including architecture, estimation, product planning, user story/requirement creation. • Experience of design and development across multiple layers of an application. • Implemented and developed new machine learning approaches and services. • Mentoring junior team members. DESIRABLE: • Good communication skills, able to communicate issues to technical and non-technical people. • Experience of Continuous Integration and Continuous Delivery techniques. • Experience with major machine learning frameworks, languages and NLP frameworks. • Experience in cleansing, filtering and re-factoring complex data from different sources. • Experience of debugging and troubleshooting live applications. • Active participation in knowledge sharing activities, both within the team and with wider non- technical audiences. • Experience of balancing technical decisions with user needs and commercial constraints. • Knowledge of cloud platforms, such as AWS and Azure, including SaaS and PaaS services.