Join Optum, a global healthcare organization dedicated to improving lives through technology. This role focuses on advancing health optimization worldwide, offering a culture of inclusion, collaboration, and growth. You will contribute to a mission-driven environment where caring, connecting, and growing together are core values. This is an opportunity to make a significant impact on the communities we serve.

Spearhead the development and deployment of AI, Machine Learning, and Generative AI strategies, with a strategic emphasis on marketing domains and the content supply chain. Collaborate across teams to define and execute AI/ML initiatives that yield tangible business outcomes. Design, build, and deploy robust, scalable AI/ML and Generative AI solutions. Drive innovation by actively adopting and integrating emerging AI technologies, frameworks, and methodologies.

Lead the seamless integration of AI/ML capabilities into products and platforms, championing best practices throughout the development lifecycle. Utilize Agile and DevSecOps for automated, continuous delivery across the AI Development Lifecycle (AIDLC). Develop and optimize solutions using advanced techniques like LLMs, RAG, AI Agents, Vector Databases, Prompt Engineering, and model fine-tuning.

Mentor teams and cultivate AI engineering expertise, standards, and governance. Architect, deploy, and manage AI solutions across major cloud environments, including AWS, Azure, and GCP. Continuously assess and implement new tools and approaches to enhance AI/ML solution delivery, ensuring compliance with all company policies and directives.

Possess a Master's degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics. Bring over 12 years of experience in Software Engineering, Data Science, Analytics, or related areas, with a minimum of 8 years specifically in AI/ML Engineering.

Demonstrate at least 3 years of recent, hands-on experience with Generative AI technologies, including OpenAI, Claude, Gemini, LangChain, AI Agents, RAG, Vector Databases, Prompt Engineering, and model fine-tuning. Key technical skills include solid expertise in AI, ML, and Generative AI solution development, proficiency with frameworks like MLflow, TensorFlow, PyTorch, Keras, and Scikit-learn.

Experience working with cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP) is essential. A deep understanding of Agile delivery methodologies, DevSecOps practices, CI/CD pipelines, and automation across the AI lifecycle is required. Proficiency in Python and other relevant programming languages for AI/ML development and data analysis is critical.