Lead AI Engineer

Requirements

• Determined - you're flexible and overcome obstacles to get the job done to achieve personal and team goals.
• Creative - you actively look for better ways to do things using the latest AI technologies to find fresh solutions to complex problems
• Honest - always constructive when giving or receiving feedback, being transparent and truthful when dealing with others
• Respectful - you treat others as you would like to be treated being encouraging, accepting and supportive to everyone you deal with
• Cooperative - you share information, knowledge and experience, understanding the mutual benefits of team working.
• Embracing our differences
• 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.

Benefits

Additional Information

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 a Lead AI Engineer within the Workday Practice at Kainos, you will play a critical role in bridging the gap between data science and software engineering to productionize AI and machine learning solutions. You will work closely with data scientists, software engineers, and product teams to deliver robust, scalable AI solutions that enhance our Workday product offerings. Your focus will be on ensuring seamless integration of AI models into production systems, optimizing performance, and maintaining the reliability of AI-driven features. Essential Experience: Extensive experience in software development, with proficiency in languages such as Python, Java, or C++. Emphasis on writing clean, efficient, and maintainable code for production-grade AI solutions. Proven experience in deploying AI/ML models to production environments, ensuring scalability, reliability, and performance. Familiarity with MLOps practices, including CI/CD pipelines, model versioning, and monitoring. Comprehensive experience with cloud platforms (AWS, Azure, or GCP) and cloud native AI tools, such as SageMaker, Vertex AI, or Azure ML Studio. Ability to design and deploy cloud-based AI solutions. Proficiency in using containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable AI solutions. Strong skills in data engineering, including building data pipelines, data wrangling, and integrating AI solutions with enterprise data systems. Exposure to agile software development practices and experience working in agile teams. Strong interpersonal skills, with the ability to collaborate with cross-functional teams, translate technical requirements into actionable solutions, and communicate effectively with both technical and non-technical stakeholders. Desirable Experience: MSc or PhD in Computer Science, Machine Learning, Software Engineering, or a related field. Familiarity with Workday APIs, data structures, and integration patterns. Experience designing and implementing generative AI solutions using large language models (e.g., OpenAI GPT, Hugging Face Transformers). Expertise in applying deep learning techniques (e.g., CNNs, RNNs, Transformers) to real-world problems. Active participation in knowledge-sharing activities such as conferences, workshops, or blogs, contributing to the AI community and fostering innovation.

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