Live opening · Posted 8 days ago

Sr Manager AI/ML Engineering

Optum (UnitedHealth) · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 8 days ago
CompanyOptum (UnitedHealth)
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SourceLinkedin
Listed8 days ago

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About the role

Description supplied by the original job listing.

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.
You will join a collaborative AI Platform team building a payer-focused agentic platform that orchestrates data, models, and workflows to support complex healthcare operations. In this role, you will provide critical onshore leadership for AI platform execution and forward deployment across Payment Integrity and Optum Real, ensuring secure, scalable delivery of reusable AI services. The team designs and delivers intelligent, agent-driven applications that review and reason over clinical and administrative data, evaluate AI outputs, and automate decision workflows, while ensuring our production systems are reliable, scalable, and continuously improving.
By applying AI to agentic workflows, deployment automation, and production observability in customer environments, you will help accelerate delivery, reduce risk, enable platform reuse, and drive repeatable revenue. We have the data and resources to make an impact on a massive scale; when our solutions are deployed, they process millions of clinical data elements and benefit millions of patients. We are a globally distributed and diverse organization with a shared passion to improve patient outcomes, enhance healthcare operations, and streamline payments. We pay close attention to detail to ensure we deliver high quality, the first time.
Primary Responsibilities:
Provide strategic and technical leadership for AI platform execution and forward deployment across Payment Integrity and Optum Real, ensuring secure, reliable, and scalable delivery of reusable AI services
Lead and inspire a high-performing team of AI/ML engineers and senior staff, fostering a culture of trust, ownership, product quality, and consistent execution excellence while setting clear AI development goals within team plans
Champion AI as a core driver of team success, strategically designing, developing, and deploying AI-powered solutions to address complex clinical and administrative healthcare challenges and deliver measurable business value
Strategically design and deliver intelligent, agentic workflows and agent-driven applications that review and reason over clinical and administrative data in customer environments
Drive engineering and operational excellence across the full development lifecycle by applying AI to deployment automation, robust automated testing, continuous integration, and production observability in customer environments
Leverage and integrate enterprise-approved AI tools to streamline engineering workflows, automate routine developer tasks, and drive continuous operational improvement
Champion the ethical use of AI across all projects, proactively embedding transparency, fairness, and accountability throughout the entire AI lifecycle of reusable services
Partner cross-functionally with product managers, customer integration teams, senior stakeholders, and enterprise leaders to represent the engineering vision, accelerate platform reuse, and drive repeatable revenue
You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Qualifications -
Required Qualifications:
Bachelor's degree or Masters in Computer Science, Software Engineering, Information Technology, Mathematics, Statistics, or a related quantitative field, or 4+ additional years of equivalent software engineering experience in lieu of a degree
12+ years of experience in Software Engineering,Data Analytics, with 3+ years dedicated to AI/ML engineering or related fields
3+ years of experience directly managing, coaching, and developing engineering teams of 5+ people, including senior engineers
Demonstrated experience leading and managing AI/ML projects from initial ideation and development through to customer-facing production delivery, deployment, and evaluation
Technical experience with major cloud platforms (AWS, Azure, or GCP) and containerization/orchestration tools (Docker, Kubernetes)
2+ years of hands-on experience with Generative AI technologies, including large language models (LLMs like OpenAI, Claude, Gemini), LangChain, AI Agents, Retrieval-Augmented Generation (RAG), Vector Databases, Prompt Engineering, and model fine-tuning
Experience with DevSecOps, automated CI/CD practices (e.g., Git, Jenkins), and proficiency in Python or other programming languages for data analysis and AI/ML development
Preferred Qualifications:
Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field
2+ years of hands-on experience with Generative AI technologies, including large language models (LLMs like OpenAI, Claude, Gemini), LangChain, AI Agents, Retrieval-Augmented Generation (RAG), Vector Databases, Prompt Engineering, and model fine-tuning
Experience applying AI to agentic workflows, deployment automation, and production observability (e.g., model monitoring, logging, and performance tracking)
Experience in establishing and enforcing AI/ML engineering best practices, design standards, and ethical guidelines
Experience in Payment Integrity, clinical operations, or healthcare claim systems
Experience managing or working with a mixed team, both onshore and offshore

Work arrangement
No

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