Director Software Engineering

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

As a Director of Technology - AI Transformation, you will be both a strategic leader and a hands-on engineer, guiding a small, high-performance team while personally contributing to the design and development of AI-first solutions. This role requires a deep technical foundation in AI/ML systems and cloud-native architectures, coupled with a startup mindset to drive innovation at scale. You will work in close collaboration with data scientists, product managers, and cloud engineers to bring complex AI products to life that improve the healthcare ecosystem globally.

Primary Responsibilities:

• Be a hands-on architect and coder, actively building AI-enabled products and platforms while guiding engineering standards and practices
• Drive end-to-end AI-driven digital transformation initiatives with ownership of architecture, implementation, and delivery
• Lead and mentor small, agile engineering teams to foster a culture of innovation, quality, and continuous improvement
• Prototype, build, and deploy scalable AI/ML solutions in real-world healthcare environments
• Apply engineering best practices for system design, development, testing, automation, and maintenance
• Develop solutions using Python, Java, with AI/ML libraries and frameworks
• Architect and implement cloud-native applications across Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure
• Drive DevOps and MLOps maturity with CI/CD pipelines, container orchestration (Docker/Kubernetes), and Infrastructure-as-Code (Terraform, CloudFormation, etc.)
• Explore and implement new tools and techniques for improved performance, observability, and operational excellence
• Collaborate across teams (data engineering, product, design) to translate AI research into customer-facing applications
• Champion a startup mentality: iterate quickly, fail fast, and scale smartly
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

• Design and fine-tune generative AI models (e.g., GPT, Gemini, Claude, Nova, etc.) for practical healthcare applications
• Develop effective prompting strategies and retrieval-augmented generation (RAG) pipelines
• Implement model tuning techniques such as LoRA, QLoRA, and RLHF to improve task performance and alignment
• Deploy and monitor optimized generative models in production using tools
• Ensure safety, ethical compliance, and robustness in generative AI outputs through testing, red-teaming, and bias mitigation

• Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree preferred)
• 12+ years of progressive experience in software engineering, with 3+ years in a technology leadership role while remaining technically hands-on
• Solid hands-on programming skills in Python, Java
• Experience in agile/start-up environments, building and launching products from 0-1
• Deep experience with cloud infrastructure and services across GCP, AWS, and Azure
• Familiarity with data pipelines and platforms (e.g., Spark, Airflow, Kafka)
• Proficiency in designing microservices architectures, using Docker, Kubernetes, and CI/CD pipelines
• Proven expertise in developing and deploying AI/ML systems into production environments
• Proven excellent interpersonal and communication skills; capable of engaging across technical and non-technical audiences

• Knowledge of healthcare data standards such as FHIR, EDI, claims, or benefits