Senior Manager AI/ML Engineering

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.

Lead the design and delivery of next-generation Agentic AI systems and GenAI products.

AI/ML Engineers code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR).Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages. Impact of work is most often at the operational or local business unit or market level.

Primary Responsibilities:

• Architect & Innovate: Define and evolve the technical architecture for Agentic AI platforms leveraging Python, LangChain/LangGraph, and frameworks like ReACT, ReWOO, RAG, and A2A
• Technical Leadership: Set the vision for prompt engineering, evaluation strategies, and reliability guardrails review designs and contribute to critical code paths when needed
• Cloud-Native Solutions: Design scalable, secure, and resilient solutions on Azure (Function Apps, Cosmos DB, AKS) with enterprise-grade observability and compliance
• Performance & Scalability: Drive optimization of multi-turn conversational agents establish benchmarks and performance KPIs
• Engineering Excellence: Champion best practices-test coverage, coding standards, CI/CD quality gates-and foster a culture of continuous improvement
• Delivery & Operations: Oversee modern DevOps practices (Docker/Kubernetes, CI/CD pipelines, security scans) and ensure production readiness
• Cross-Functional Collaboration: Partner with product, platform, and backend teams to integrate APIs and microservices define SLAs and telemetry standards
• Monitoring & Reliability: Implement observability for AI agent behavior (latency, hallucination rate, safety compliance) define SLOs and operational playbooks
• Knowledge Management: Maintain architecture decision records, design documentation, and operational guides in a shared knowledge base
• Leadership & Mentorship: Build and mentor a high-performing engineering team facilitate architecture reviews, roadmap planning, and release readiness
• Provides leadership to and is accountable for the performance of managers and/or senior level professional staff
• 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 regard 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 in Computer Science, Engineering, or related field advanced degree preferred.
• 12+ years in software engineering with experience in AI/ML systems or large-scale distributed platforms proven leadership in technical architecture and delivery
• AI/ML Expertise:
  • Solid hands-on proficiency in Python and AI agent frameworks (LangChain, LangGraph, ReACT, ReWOO, RAG)
  • Deep understanding of LLM-driven architectures, prompt engineering, evaluation metrics, and reliability/safety guardrails
• Cloud & Architecture:
  • Extensive experience with Azure cloud-native services (Function Apps, Cosmos DB, AKS) and microservices architecture
  • Familiarity with event-driven, serverless, and scalable design patterns
• DevOps & Security:
  • Proficiency in containerization (Docker/Kubernetes) and CI/CD pipelines with security/compliance gates
  • Knowledge of observability frameworks, telemetry, and operational resilience
• Performance & Optimization:
  • Expertise in profiling, benchmarking, and optimizing for latency, throughput, and cost efficiency
• Quality Engineering:
  • Solid testing discipline (pytest), coverage targets, static analysis, and continuous quality gates
• Leadership & Collaboration:
  • Demonstrated ability to lead technical decisions, mentor engineers, and drive engineering excellence

  • Excellent communication and stakeholder management skills ability to align architecture with business goals