AI Engineer - Workday Products
On-siteBelfast, Northern Ireland, United Kingdom or Birmingham, England, United Kingdom
EXPIREDBelfast, Northern Ireland, United Kingdom or Birmingham, England, United KingdomOn-siteFull TimeSenior LevelBachelors DegreeLarge
Full TimeSenior LevelBachelors DegreeLarge
Job Summary
Produce and integrate AI and machine learning solutions into production systems under senior engineering guidance. Collaborate with data scientists, software engineers, and product teams to deliver robust, scalable AI features for Workday offerings like Kainos Smart and Employee Document Management. Develop clean, maintainable code using Python while gaining foundational MLOps, cloud deployment, and software engineering skills. Handle sensitive data in accordance with responsible AI and security practices.
Required Qualifications
- Typically 2+ years of relevant industry experience
- Foundational experience in software development
- Working knowledge of Python (or a similar language such as Java or C++)
- Willingness to develop clean, maintainable code under guidance
- Some exposure to deploying or supporting AI/ML models
- Interest in developing MLOps skills (CI/CD, model versioning, monitoring)
- Awareness of responsible AI, security, and data privacy practices
- 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 (AWS, Azure, or GCP)
- Some exposure to agile software development practices
- Good interpersonal skills
- Enthusiasm for collaborating with cross-functional teams
- Ability to communicate technical ideas clearly
Desired Qualifications
- BSc in Computer Science, Machine Learning, Software Engineering, or a related field
- Personal, academic, or internship projects demonstrating an interest in AI/ML productionisation
- Familiarity with Workday APIs, data structures, and integration patterns
- Exposure to generative AI concepts or tools (e.g., OpenAI GPT, Hugging Face Transformers)
- Basic awareness of deep learning concepts (CNNs, RNNs, Transformers)
- Enthusiasm for participating in team knowledge-sharing activities, such as internal show-and-tells or learning sessions
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