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.
At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive. We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are. We also believe every candidate deserves a level playing field.
Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out.
We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.
Skills Required
- Proficiency designing, building, testing, and maintaining production software applications integrating AI services and data science models
- Proficiency applying mathematical principles to gain insight from data
- Experience applying development patterns for security, scalability, and performance
- Experience contributing to technical decisions, architecture, estimation, product planning, and user story or requirements creation
- Experience designing and developing across multiple application layers
- Experience implementing and developing machine learning approaches and services
- Experience mentoring junior team members
- Good communication skills with technical and non-technical audiences
- Experience with Continuous Integration and Continuous Delivery techniques
- Experience with major machine learning frameworks, programming languages, and NLP frameworks
- Experience cleansing, filtering, and refactoring complex data from different sources
- Experience debugging and troubleshooting live applications
- Participation in knowledge-sharing activities
- Experience balancing technical decisions with user needs and commercial constraints
- Knowledge of cloud platforms such as AWS and Azure, including SaaS and PaaS services
Kainos Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Kainos and has not been reviewed or approved by Kainos.
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Healthcare Strength — Private healthcare, access to trained counsellors/EAP, and broader wellbeing initiatives are prominently offered across regions. Company materials frame support across emotional, physical, social, career and financial wellbeing, with UK references to Bupa coverage.
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Leave & Time Off Breadth — Hybrid/flexible hours, generous vacation packages, and parental leave are emphasized in careers materials. Some regions also highlight volunteering time and flexibility that support work–life balance.
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Equity Value & Accessibility — Annual share awards and employee share plans (e.g., free shares, Sharesave) are widely promoted, with cash equivalents where plans aren’t available. These programs broaden ownership participation beyond base pay.
Kainos Insights
What We Do
At Kainos we use technology to solve real problems for our customers, overcome big challenges for businesses, and make people’s lives easier. We build strong relationships with our customers and go beyond to change the way they work today and the impact they have tomorrow. Our two specialist business areas, Digital Services and the Workday Practice, work globally for clients across healthcare, commercial and the public sector to make the world a little bit better, day by day.
