Your work days are brighter here.
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
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About the Team
Our Globalisation Platform Engineering organisation's mission is to lead the internationalisation and localisation of Workday products and peripheral content by leveraging innovative and new Agentic AI capabilities. Our ambition is to provide a fit-for-purpose language experience to our customers by partnering with internal teams through innovative and emerging technology capabilities!
Our diverse and globally distributed engineering organisation is composed of independent and autonomous problem solvers across engineering and product management. We are passionate about using groundbreaking AI technologies to drive innovation and efficiency leading to a brighter Workday for all. We value teamwork, effective communication and accountability.
About the Role
You will play a key part in designing and developing the future localisation and Agentic AI capabilities for Workday to achieve our internationalisation and localization strategies by leveraging the power of AI. You will lead by example, demonstrating architecture and product development best practices, while mentoring and empowering your fellow team members to achieve success.
- Building Agentic AI solutions: You will collaborate on the creation and implementation of sophisticated AI agents, including fine-tuning models and developing sophisticated Agentic RAG solutions to address complex business challenges and enhance our products.
- Mentoring and guiding engineers: You will coach and mentor fellow engineers, fostering a culture of innovation and teamwork.
- Collaborating with product and engineering: You'll partner with product managers and engineering teams to collaborate on product roadmaps and ensure successful integration of AI solutions.
- Staying ahead of the curve: You will keep yourself informed of the latest advancements in machine learning and AI research, identifying and evaluating new technologies for potential adoption.
About You
Basic Qualifications:
- 7+ years experience with the development of SaaS products, including familiarity with Object Oriented languages, devops and related technologies and best practices
- Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, maths or equivalent.
- 3 or more years of experience developing, deploying, and supporting high-performance systems in production.
- 3 or more years of experience delivering AI products, including taking a product through design, implementation, and to production.
- 3 or more years of developing AI driven features with Python, JVM, and Linux.
- Proven theoretical and practical understanding of statistical analysis and machine learning algorithms, natural language processing, especially for supervised, unsupervised and self-supervised methods.
- Practical experience with generative models, large language models (LLM), retrieval augmented generation (RAG) systems, transformer neural networks.
Other Qualifications:
- 3 or more years of experience with industry tools used to build scalable machine learning systems, such as AWS, SQL, Elasticsearch/Open Search, Kubernetes, Docker and/or Spark
- Experience designing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labelling, model development, validation, deployment, and ongoing monitoring.
- Experience with fine-tuning models including identifying and curating datasets as well as experimenting with models for iterative improvement
- Resilience to obstacles, and ability to solve problems independently.
Workday is proud to be an equal opportunity workplace.
Further, pursuant to applicable local ordinances, Workday will consider for employment qualified applicants with arrest and conviction records.
You may view the Workday's Pay Transparency Policy, and Equal Employment Opportunity is the Law notice, by clicking on their corresponding links.
Workday is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans during our application process. If you need assistance or an accommodation due to a disability, contact us at [email protected].
Our Approach to Flexible Work
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
