[Hiring] Principal I O Engineering @UnitedHealth Group

Role Description

The Optum Technology Digital team is on a mission to disrupt the healthcare industry, transforming UHG into an industry-leading Consumer brand. We deliver hyper-personalized digital solutions that empower direct-to-consumer, digital-first experiences, educating, guiding, and empowering consumers to access the right care at the right time.

As we drive this transformation, we're revolutionizing customer interactions with the healthcare system, leveraging AI, cloud computing, and other disruptive technologies to tackle complex challenges.

You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities

• Technical Leadership & Strategy
  • Set direction for future technologies and partner with application teams to develop technology roadmaps.
  • Develop proof-of-concepts for new products and define centers of excellence.
  • Anticipate and proactively improve systems and future designs for increased performance and availability.
  • Develop strategy for infrastructure/platform lifecycle management and resource forecasting.
  • Research emerging technologies, evaluate feasibility, and recommend solutions that deliver business value.
• Infrastructure & Platform Management
  • Write integrated automation code at an expert level across multiple platforms.
  • Articulate technical trade-offs of different IaaS, PaaS, and SaaS designs.
  • Build instrumentation and diagnostics demonstrating business value of the CI/CD chain.
  • Lead strategy development for DevOps and Site Reliability Engineering practices.
  • Consult on technology solutions meeting security, scalability, reliability, and feasibility requirements.
• AI Builder & Development
  • Design, develop, and deploy AI/ML pipelines and infrastructure to support enterprise AI initiatives.
  • Build and maintain AI tooling, frameworks, and platforms that enable teams to develop and deploy AI solutions.
  • Implement and optimize AI feature stores, model registries, and MLOps workflows.
  • Integrate AI capabilities into existing infrastructure and CI/CD pipelines.
  • Evaluate and implement AI-powered automation tools to enhance operational efficiency.
  • Collaborate with data science teams to productionize ML models at scale.
  • Develop monitoring and observability solutions for AI/ML systems performance and drift detection.
• Collaboration & Mentorship
  • Serve as an escalation point for complex issues, problems, and solutions.
  • Provide guidance, assistance, and consultation to engineering teams (SME, mentor).
  • Translate technical concepts into business terms for stakeholders.
  • Lead collaborative efforts to advance customer and business interests.
  • Coach others on troubleshooting skills and develop troubleshooting guides.
• Security & Quality
  • Champion compliance with security standards and regulations.
  • Proactively identify and address security gaps in solution design and delivery.
  • Research security trends and emerging threats; incorporate findings into solutions.
  • Lead quality improvement processes and drive a quality culture by example.
  • Partner with stakeholders to develop secured products using DevSecOps principles.

Qualifications

• 8+ years in infrastructure/operations engineering or related field.
• 5+ years of experience in infrastructure platforms (compute, storage, networking, virtualization).
• 5+ years of experience in automation and infrastructure-as-code.
• 5+ years of experience with container orchestration (Kubernetes, etc.).
• Experience with monitoring, observability, and SRE practices.
• Hands-on experience with AI/ML platforms and tools (e.g., Anthropic, OpenAI, Amazon Bedrock, etc.).
• Understanding of CI/CD pipelines and deployment automation.
• Proficiency in public and private cloud platforms (AWS, Azure, GCP).

Preferred Qualifications

• Experience defining and driving observability metrics and SLOs.
• Experience with capacity optimization and resource forecasting.
• Experience with LLM integration, prompt engineering, and generative AI tooling.
• Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
• Experience building and maintaining ML pipelines and MLOps infrastructure.
• Knowledge of AI governance, model monitoring, and responsible AI practices.
• Familiarity with multiple IaaS, PaaS, and SaaS service offerings.
• Familiarity with AI feature engineering, model deployment, and serving architectures.
• Proven background in developing DevSecOps culture and practices.
• Proven history of contributing to internal/external tech communities (open source, best practices).
• Proven ability to communicate and negotiate direction with executive leadership.
• Proven solid analytical skills—drawing correlations from non-standard data sets.
• Demonstrated experience leading technical initiatives across multiple teams.
• Proven track record of developing and implementing technology strategies.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase.
• 401k contribution (all benefits are subject to eligibility requirements).

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.