Sr Manager, Software Engineering - AI​/Conversational Platforms - Hybrid; Minneapolis, Char

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives.

Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.

Software engineering at Optum Technology applies disciplined engineering principles to architect, build, and operate scalable, high-impact software systems.

The Senior Manager, Software Engineering will lead multiple engineering teams responsible for delivering enterprise-grade AI-driven voice, IVR, and conversational platform capabilities. This role combines technical leadership, organizational leadership, and execution ownership, ensuring alignment with product strategy, customer outcomes, and enterprise architecture.

This leader will drive end-to-end delivery, organizational maturity, and innovation across AWS-based conversational platforms, while embedding a solid quality engineering (QE) mindset, operational excellence, and AI/ML rigor into all aspects of delivery.

You’ll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

• Lead and scale multiple engineering teams, driving delivery across complex, cross-functional initiatives
• Establish engineering strategy aligned with Optum Technology and AI 10.0 objectives
• Provide organizational leadership, including hiring, talent development, performance management, and succession planning
• Set clear engineering standards, drive accountability, and foster a culture of ownership and continuous improvement
• Serve as a senior technical leader and escalation point for complex system and architectural challenges
• Influence enterprise engineering practices, platform strategy, and long-term architectural direction

• Own delivery of enterprise conversational AI platforms supporting voice, IVR, and chatbot experiences
• Drive adoption and scaling of technologies including:
  • Amazon Connect
  • Amazon Lex (V2)
• Partner with AI/ML teams to operationalize:
  • NLP pipelines
  • LLM integrations (Amazon Bedrock, OpenAI, or similar)
  • Prompt engineering and evaluation strategies
• Ensure production-grade AI systems with measurable outcomes across:
  • Accuracy
  • Reliability
  • Customer experience

• Oversee architecture and delivery of cloud-native systems leveraging:
  • AWS Lambda
  • API Gateway
  • DynamoDB
  • Event-driven architectures
• Ensure systems are scalable, resilient, secure, and cost-efficient
• Drive platform standardization, reuse, and alignment with enterprise cloud strategy
• Partner with enterprise architecture teams to govern design decisions and technical trade-offs

• Own delivery across multiple concurrent programs and work streams
• Drive planning and execution across:
  • Dependencies
  • Risks and mitigation strategies
  • Milestones and roadmap alignment
• Collaborate with product, architecture, QE, and operations teams to ensure end-to-end delivery
• Establish and track success metrics tied to product adoption, performance, and business outcomes
• Ensure production readiness, operational support models, and continuous optimization

• Embed a quality-first engineering culture across all teams
• Define and enforce enterprise quality standards across:
  • Functional performance
  • Reliability and scalability
  • AI/ML model effectiveness
• Champion advanced testing strategies for conversational AI:
  • Intent accuracy and NLU validation
  • Dialog and conversation flow testing
  • Edge case and failure scenario handling
  • Regression and continuous validation pipelines
• Partner with QE to implement:
  • Automated test frameworks
  • Synthetic traffic and simulation
  • Golden dataset and replay-based validation models
• Use telemetry and data insights to continuously enhance system performance and user experience

• Drive innovation across AI, cloud, and conversational technologies
• Evaluate and introduce new tools, frameworks, and engineering methodologies
• Promote reuse through shared services, frameworks, and automation
• Contribute to enterprise standards, best practices, and engineering governance
• Lead initiatives to improve developer productivity, system reliability, and operational efficiency

• Operate as an enterprise leader influencing strategy, execution, and outcomes
• Anticipate customer needs and proactively drive innovative solutions
• Lead through ambiguity and complexity with solid decision-making
• Build and develop high-performing, diverse engineering teams
• Drive alignment across multiple stakeholders and…