Kainos
AI Engineer - Workday Products
Job Description
Salary: £28,000 - 51,000 per year
Requirements:- Typically 2+ years of relevant industry experience.
- Foundational experience in software development, with working knowledge of Python or a similar language such as Java or C++, and a willingness to develop clean, maintainable code under guidance.
- Some exposure to deploying or supporting AI/ML models through academic projects, internships, or early career experience, with an interest in developing MLOps skills such as CI/CD, model versioning, and monitoring.
- Awareness of responsible AI, security, and data privacy practices, with the ability to follow agreed guidelines such as handling sensitive data correctly, using approved tools, and raising potential risks to senior colleagues.
- Basic understanding of cloud platforms such as AWS, Azure, or GCP; exposure to cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio is a plus.
- Awareness of containerisation technologies such as Docker; exposure to orchestration tools such as Kubernetes is beneficial but not essential.
- Emerging data engineering skills, such as working with data pipelines or data wrangling, gained through coursework, internships, or personal projects.
- Some exposure to agile software development practices, for example through internships, university projects, or previous roles.
- Good interpersonal skills, with enthusiasm for collaborating with cross-functional teams and communicating technical ideas clearly.
- BSc in Computer Science, Machine Learning, Software Engineering, or a related field is desirable.
- Personal, academic, or internship projects demonstrating an interest in AI/ML productionisation are desirable.
- Familiarity with Workday APIs, data structures, and integration patterns is an advantage but not required.
- Exposure to generative AI concepts or tools such as OpenAI GPT or Hugging Face Transformers through coursework or self-directed learning is desirable.
- Basic awareness of deep learning concepts such as CNNs, RNNs, and Transformers gained through study or personal exploration is desirable.
- Enthusiasm for participating in team knowledge-sharing activities such as internal show-and-tells or learning sessions is desirable.
- Support the team in productionising AI and machine learning solutions.
- Work closely with and under the guidance of senior engineers to help integrate AI models into production systems.
- Collaborate with data scientists, software engineers, and product teams to deliver robust, scalable AI solutions.
- Help deliver AI solutions that enhance our Workday product offerings, including Kainos Smart, Employee Document Management, and Pay Transparency Analyzer.
- Build foundational skills in MLOps, cloud deployment, and software engineering practices while contributing to real-world AI solutions.
- AI
- AWS
- Azure
- CI/CD
- Cloud
- Docker
- GCP
- Support
- Java
- Kubernetes
- Machine Learning
- MLOps
- Python
- Security
More:
We are Kainos, a people-first company of problem solvers, innovators, and collaborators driven to create real impact. We work on transforming digital services, delivering Workday solutions, and pushing the boundaries of technology together. Our diverse, ambitious team values creativity and collaboration, and we support growth in an inclusive environment where contributions make a difference. This Associate AI Engineer role sits within our Workday Products division and offers the opportunity to develop foundational skills while contributing to products such as Kainos Smart, Employee Document Management, and Pay Transparency Analyzer. We also actively support diversity, equity, and inclusion, and our friendly talent acquisition team can help with accommodations or adjustments during the recruitment process.
last updated 36 week of 2026
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About Kainos
Kainos
Birmingham
IT
Skills & Technologies
Inferred from job description
Salary Insight
£39,500
This role
£60,000
UK median
This salary is 34% below the UK median for Software Engineers (£60,000/yr).
Based on 2024–2025 UK technology sector benchmarks