Senior AI/ML Engineer

About Optum

Join Optum, a leading health services and technology company part of UnitedHealth Group (Fortune 6), dedicated to improving health care delivery worldwide. With a global team of over 115,000, Optum combines people, technology, data, and action to enhance healthcare quality, efficiency, and accessibility. Our core values include integrity, compassion, relationships, innovation, and performance. Diversity and inclusion are fundamental, and we maintain a drug-free workplace.

Role Summary and Key Duties

The Senior AI/ML Engineer will lead the full lifecycle development of AI and machine learning solutions driving scalable, secure, and reliable software implementations within enterprise healthcare systems. Responsibilities include designing, testing, deploying, maintaining, and enhancing these AI-powered products, driving best practices in AI engineering and operations (AI MLOps), and ensuring compliance with security, privacy, ethical, and regulatory requirements.

• Lead the design, development, testing, deployment, and ongoing improvement of AI/ML solutions by translating models into enterprise-grade software.
• Act as technical lead for complex AI/ML projects, managing end-to-end delivery, production deployment, monitoring, and optimization.
• Build responsible AI systems and reusable services adhering to enterprise standards on security, privacy, ethics, quality, and compliance.
• Develop advanced AI features such as Generative AI, predictive analytics, automation, chatbots, conversational AI, and intelligent workflow tools.
• Promote AI and MLOps best practices to ensure production readiness, observability, resilience, and continuous improvement across models and services.
• Drive modern engineering methodologies including automation, code reuse, CI/CD, test automation, and operational excellence.
• Collaborate with product managers, architects, engineering leaders, and technology teams to align AI solutions with business goals and enterprise strategy.
• Create and maintain detailed architecture and integration diagrams for AI/ML systems and services.
• Champion enterprise security, privacy, and compliance by identifying and mitigating technical, operational, data, and model risks.
• Ensure quality delivery with maintainable code, reliable services, clear documentation, production readiness, and measurable outcomes.
• Mentor and coach engineering teams on AI/ML technologies, frameworks, MLOps, and ethical AI principles.
• Utilize enterprise-approved AI tools to streamline workflows, automate tasks, and enhance delivery efficiency.
• Work closely with cloud and platform teams to integrate AI into cloud-native, digital-first solutions at scale.
• Manage independent prioritization, planning, risk assessment, and delivery of AI engineering initiatives.
• Effectively communicate complex AI/ML technical concepts, tradeoffs, risks, and results to diverse stakeholders including senior leadership.
• Continuously evaluate emerging AI/ML trends, tools, and frameworks to optimize solutions and foster innovation.
• Comply with company policies including employment terms, potential role or location changes, flexible work arrangements, and other directives.

Qualifications and Skills

• Bachelor's degree in Computer Science or a related technical discipline.
• Minimum 7 years of professional software engineering experience using Python, Java, Scala, or similar.
• At least 5 years of hands-on experience in developing AI/ML solutions including large language models (LLMs), Generative AI, traditional machine learning models, and deploying RAG pipelines, agentic workflows, and orchestration layers.
• Background in healthcare industry software development preferred.
• Experience architecting cloud-native solutions on Azure.
• Full-stack engineering skills with proficiency in backend and frontend technologies.
• Strong expertise in chatbots, conversational AI, and NLP-driven applications.
• Deep knowledge of security controls, access management, logging, monitoring, performance tuning, disaster recovery, and production operations.
• Proven capability to design and deliver end-to-end AI services including backend APIs, orchestration layers, and UI integration targeting claims and operations users.
• Experience developing scalable backend services using Java (Spring Boot) and modern API frameworks.
• Skill in integrating web applications using frontend frameworks such as React or similar for AI-enhanced user experiences.
• Solid expertise building AI components leveraging Azure cloud services, foundation models, embeddings, vector stores, and best practices in prompt engineering.
• Experience with agent-based architectures (AgentCore/agentic cloud patterns) supporting workflows like claims adjudication, exception handling, and human-in-the-loop scenarios.
• Competence in ongoing model performance evaluation, hallucination risk management, explainability, and operational metric monitoring in production environments.