Sr Manager, Software Engineering - AI / Conversational Platforms - Hybrid (Minneapolis, Charlotte, Austin )

UnitedHealth Group•Minneapolis, MN

1d•$112,700 - $193,200•Hybrid

About The Position

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.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)
12+ years of software engineering experience, with 5+ years in engineering management or leadership roles
5+ years of experience leading multiple teams delivering large-scale, distributed systems
5+ years of experience designing and delivering cloud-native applications (AWS preferred)
3+ years of experience delivering AI/ML or conversational platforms in production environments
2+ years of experience with AWS technologies including Amazon Connect, Lex (V2), Lambda, and API Gateway
Experience building and scaling engineering teams and delivery organizations
Experience with quality engineering, testing strategies, and production operations
Reside in Chicago, Minneapolis, Charlotte, Santa Ana, Austin (role is hybrid / onsite)

Nice To Haves

Experience in healthcare technology or regulated environments
Deep understanding of voice platforms, IVR systems, and speech technologies
Experience with LLMs, GenAI systems, and evaluation frameworks
Familiarity with CI/CD pipelines, DevOps, and observability platforms
Experience leading enterprise-scale AI transformation initiatives (e.g., AI 10.0)
Solid strategic thinking and organizational leadership skills
Demonstrated ability to influence at executive levels
Experience operating in large, matrixed enterprise environments
Passion for innovation and continuous improvement in AI-driven systems

Responsibilities

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 workstreams
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 organizations
Communicate effectively with senior leadership and executive stakeholders
Deliver measurable impact across technology, product, and business dimensions