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Join Kainos and Shape the Future 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. As an Associate AI Engineer within Kainos’ Workday Products division , you will support the team in productionising AI and machine learning solutions, working closely with and under the guidance of senior engineers to help integrate AI models into production systems. You will work closely with data scientists, software engineers, and product teams to deliver robust, scalable AI solutions that enhance our Workday product offerings – including Kainos Smart (Smart Test, Smart Audit and Smart Shield), Employee Document Management and Pay Transparency Analyzer. T his is an opportunity to build foundational skills in MLOps , cloud deployment, and software engineering practices while contributing to real-world AI solutions that enhance our Workday product offerings. Essential Experience: 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 (CI/CD, model versioning, 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 (AWS, Azure, or GCP); exposure to cloud-native AI tools (e.g., SageMaker, Vertex AI, Azure ML Studio) is a plus. Awareness of containerisation technologies (e.g., Docker); exposure to orchestration tools (e.g., 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, e.g. through internships, university projects, or previous roles. Good interpersonal skills, with enthusiasm for collaborating with cross-functional teams and communicating technical ideas clearly. Desirable Experience: 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 is an advantage but not required . Exposure to generative AI concepts or tools (e.g., OpenAI GPT, Hugging Face Transformers) through coursework or self-directed learning. Basic awareness of deep learning concepts (CNNs, RNNs, Transformers) gained through study or personal exploration. Enthusiasm for participating in team knowledge-sharing activities, such as internal show-and-tells or learning sessions. Embracing our differences 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.