AI EngineerleadfulltimeIT Services and IT Consulting and Business Consulting and ServicesPythonJavaC++AWSAzureGCPDockerKubernetesposted
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An exciting opportunity is available for an experienced Lead AI Engineer to drive the development and deployment of cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) solutions within a market-leading Workday product portfolio.
Working at the intersection of AI engineering, software development and MLOps, the successful candidate will be responsible for transforming machine learning models into secure, scalable, production-ready applications. Collaborating closely with data scientists, software engineers and product specialists, they will help deliver innovative AI-powered capabilities that enhance enterprise Workday solutions.
This role is ideally suited to an experienced engineer with a passion for building robust AI systems, leveraging cloud technologies and integrating intelligent solutions into enterprise-grade software platforms.
Key Responsibilities
* Design, develop and deploy production-ready AI and machine learning solutions that are scalable, resilient and high performing.
* Partner with cross-functional teams including data science, engineering and product management to deliver AI-powered features and capabilities.
* Integrate machine learning models into enterprise software products while ensuring reliability, maintainability and operational excellence.
* Build and optimise AI deployment pipelines using modern MLOps practices, including automated testing, continuous integration, continuous deployment (CI/CD), model versioning and monitoring.
* Develop cloud-native AI solutions using industry-leading platforms and services.
* Create and maintain robust data pipelines to support AI workloads, enabling efficient data processing and seamless integration with enterprise systems.
* Champion engineering best practice, code quality and continuous improvement across AI development initiatives.
* Contribute to architectural decisions that support the long-term scalability and evolution of AI-enabled products.
Essential Skills \& Experience
* Extensive commercial experience in software engineering with strong programming skills in Python, Java and/or C++.
* Demonstrable success deploying AI and Machine Learning models into production environments with a focus on scalability, reliability and performance.
* Strong understanding of MLOps, including CI/CD pipelines, model lifecycle management, monitoring and automated deployment.
* Hands-on experience with major cloud platforms including AWS, Microsoft Azure or Google Cloud Platform (GCP) together with cloud-native AI services such as Amazon SageMaker, Azure Machine Learning or Vertex AI.
* Experience using Docker, Kubernetes and containerised application architectures to deploy and manage AI workloads.
* Excellent data engineering skills, including designing data pipelines, data transformation and integration with enterprise data platforms.
* Experience working within Agile software development environments.
* Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into practical business solutions while collaborating effectively across multidisciplinary teams.
Desirable Experience
* Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering or a related discipline.
* Experience working with Workday APIs, integrations and data models.
* Practical experience designing and implementing Generative AI solutions using Large Language Models (LLMs) such as OpenAI GPT or Hugging Face Transformers.
* Strong understanding of deep learning techniques including Transformers, CNNs and RNNs, with experience applying these technologies to real-world business challenges.
* Active involvement within the AI community through conferences, technical publications, blogs, workshops or open-source contributions.