Senior Software Engineering Lead - Python, react js, AI/ML

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.

We are looking for a Full Stack engineer with strong hands-on experience in full stack development, Python, AI/ML, and cloud-native engineering. The role will focus on building internal tools, automation frameworks, AI-enabled testing capabilities, and quality intelligence solutions for the Amazon Connect platform and contact center ecosystem.

The ideal candidate should have strong experience in front-end and back-end development, hands-on knowledge of Python, Flask APIs, microservices, cloud services such as AWS or Azure, and practical understanding of LLMs / Generative AI for building intelligent automation solutions. Contact center experience is preferred, with at least working knowledge of IVR, call routing, SIP/telephony flows, CRM integrations, and downstream systems.

Primary Responsibilities:

• Design and develop internal tools and frameworks to improve end-to-end testing, feature validation, and release readiness for the Amazon Connect platform
• Build AI-enabled capabilities using LLMs, AI/ML models, and automation techniques to support intelligent test execution, defect detection, test optimization, and quality insights
• Develop automation solutions using Python, Flask APIs, LLMs, and AI services to reduce manual effort and improve engineering productivity
• Develop and maintain front-end components such as dashboards, visualizations, workflow-driven interfaces, and platform health views
• Develop and maintain back-end services, APIs, microservices, and data pipelines to support automated testing workflows
• Work with cloud platforms such as AWS or Azure, including services like AWS Lambda, DynamoDB, API Gateway, S3, CloudWatch, or equivalent Azure services
• Integrate testing and quality frameworks with CI/CD pipelines to enable continuous testing and automated release validation
• Apply AI/ML and LLM-based approaches to predict failure patterns, identify defects, optimize test coverage, and generate quality insights
• Collaborate with engineering, platform, product, and AI teams to translate quality and operational needs into scalable technical solutions
• Ensure all solutions align with enterprise architecture, security, compliance, and AI governance standards
• Contribute to reusable, scalable quality engineering capabilities across multiple lines of business
• 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 degree in Computer Science or Similar field
• Experience in full stack development, with hands-on ownership of design, development, and delivery
• Solid hands-on experience in Python development
• Experience building APIs using Flask, FastAPI, or similar Python-based frameworks
• Solid experience in back-end development, including APIs, microservices, data processing components, and integration services
• Hands-on experience in front-end development, including UI design, dashboards, visualizations, and workflow-driven interfaces
• Experience building internal tools, platforms, automation frameworks, analytics solutions, or operational efficiency tools
• Practical experience using LLMs / Generative AI to build automation, decision-support, test generation, defect analysis, or workflow optimization capabilities
• Experience with AI/ML development or applied ML, including integrating AI/ML models, AI services, or LLM APIs …