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.
Primary Responsibilities:
- Design, develop, test, and deploy endtoend fullstack applications, including user interfaces, backend services, APIs, and data layers, supporting AI/ML and datadriven use cases
- Build and maintain scalable frontend experiences using modern web frameworks (e.g., React, Angular, or similar) that integrate seamlessly with backend and AIpowered services
- Develop and maintain backend services and REST/GraphQL APIs using Pythonbased frameworks (e.g., FastAPI, Flask) or equivalent Java/NET technologies
- Build and operate endtoend pipelines that integrate data ingestion, data processing, model inference, and application services
- Collaborate with data scientists and ML engineers to productionize AI/ML models, exposing them through secure, welldesigned APIs and fullstack applications
- Develop and integrate Generative AI and LLMbased features (e.g., chat interfaces, copilots, intelligent workflows) using tools such as Hugging Face, LangChain, and OpenAI APIs
- Work with largescale and relational datasets using PySpark, Databricks, Pandas, NumPy, and SQL, and integrate data services into userfacing and backend applications
- Design and implement authentication, authorization, and secure data access patterns across frontend, backend, and AI services
- Deploy, monitor, and scale fullstack and AI applications on cloud platforms such as Azure (Azure AI, Azure ML) and GCP, leveraging cloudnative services
- Implement CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), and MLOps/DevOps best practices to ensure reliable and repeatable deployments
- Build or integrate conversational AI and intelligent user experiences, ensuring usability, performance, and responsible AI practices
- Partner with product managers, UX designers, data teams, and platform engineers to deliver secure, highquality, usercentric solutions aligned with business needs
- Participate in architecture and design reviews, contributing to system scalability, maintainability, and performance across the full stack
- Stay current with emerging fullstack development, AI/ML, cloud, and software engineering technologies, and apply them pragmatically
- 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
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 8+ years of experience in software engineering with strong backend and/or fullstack development experience
- Solid programming experience in Python experience with Java and/or NET is a plus
- Proven experience building fullstack applications, including frontend frameworks (e.g., React, Angular), backend services, APIs, and databases
- Experience working with AI/ML or dataintensive applications in production, including model integration and inference at scale
- Handson experience with cloud platforms such as Azure, GCP, or AWS, including cloudnative application deployment
- Solid experience with SQL, data modeling, and largescale data processing tools
- Experience with ML deployment, MLOps, and DevOps practices (MLflow, CI/CD, Docker, Kubernetes)
- Experience in healthcare or regulated environments is preferred, with an understanding of security and compliance requirements
- Familiarity with API design, microservices architecture, and distributed systems
- Exposure to Generative AI, LLMs, and conversational AI, including userfacing integrations, is a strong plus
- Proven solid problemsolving, communication, and crossfunctional collaboration skills, with the ability to own features from design through production
Preferred Qualifications:
- Experience on the following
- Design, build, and productionize AI solutionsfor UC and ITSM workloads (e.g., Microsoft Teams Calling, Cisco WebEx Calling Cloud, ServiceNow) Work includes analytics, and automation, with strong emphasis on Responsible AIand reliability in realtime environments
- Familiarity with QoE analyticsfor UC (MOS, jitter/latency analysis) and linking quality signals to AI workflows
- Experience with Copilot Studio/Pluginsor enterprise agent frameworks to expose UC automations to end users securely
