Lead AI or ML Engineer

Optum; Gurugram District; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Optum is seeking an experienced AI/ML Platform Engineer to lead productionization of AI/ML systems on Azure and similar clouds. You will define data pipelines, model-serving APIs, and CI/CD practices while ensuring SLAs for latency and throughput.

Strong Python, Docker, and Kubernetes skills are essential for building scalable automation and tooling across distributed environments. The role requires 8+ years’ experience, a solid software foundation, and experience operating in regulated

Qualifications

• 8+ years building and operating production systems with real-world constraints.
• Hands-on experience with Azure cloud services, infrastructure management and cloud-native deployment.
• Experience designing and operating production APIs and model-serving endpoints under SLAs.
• Experience building CI/CD pipelines and managing model versioning and registries.
• Experience implementing observability: logging, metrics, alerting, drift detection.
• Solid Python software engineering fundamentals with automation and debugging skills.

Responsibilities

• Lead productionization of AI/ML systems on Azure across the full experimentation to deployment cycle.
• Define architecture and standards for data pipelines, learning workflows, and model-serving APIs.
• Design, deploy, and operate production model-serving APIs with clear latency, throughput, and availability SLAs.
• Build and maintain Python-based automation, tooling, and services for AI/ML workflows.
• Define CI/CD pipelines and engineering standards for code, data, and models; manage drift monitoring.

Skills

Production systems

Azure cloud services

CI/CD pipelines

Observability

Python

Docker

Kubernetes

Education

Undergraduate degree

Tools

GitHub Actions

Job description

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.

Primary Responsibilities:

• Lead product ionization of AI/ML systems on Azure and other cloud platforms, supporting the full journey from experimentation to deployment
• Define architecture and standards for data pipelines, learning workflows, and model-serving APIs across AI/ML systems
• Design, deploy, and operate production model-serving APIs across batch and real-time serving patterns, with clear SLAs for latency, throughput, and availability
• Build and maintain Python-based automation, tooling, and services supporting AI/ML workflows and deployments
• Define and maintain CI/CD pipelines and engineering standards for AI/ML workflows (code, data, and models)
• Containerize and orchestrate AI/ML workloads using Docker and Kubernetes, with infrastructure managed as code
• Own the design and maintenance of Dev / Stage / Prod environments on Azure
• Govern management of model artifacts, registries, and feature/representation stores
• Lead monitoring of system health, data drift, and model drift with alerting and remediation strategies
• Own post-deployment support, incident response, and continuous improvement
• 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 regards 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:

• Undergraduate degree or equivalent experience
• 8+ years of experience building and operating production systems with real-world constraints
• Hands-on experience with Azure cloud services, infrastructure management, and cloud-native deployment
• Experience designing and operating production APIs and model-serving endpoints under defined SLAs and failure modes
• Experience building CI/CD pipelines (e.g., GitHub Actions) and managing model versioning and registries
• Experience implementing observability for production systems: logging, metrics, alerting, and drift detection
• Solid software engineering fundamentals in Python, with solid software design, automation, and debugging skills
• Proficiency with Docker, Kubernetes, and workflow orchestration for containerized workloads

Preferred Qualifications:

• Infrastructure as Code experience (Terraform, Bicep, or equivalent)
• Experience with vector and NoSQL databases, RAG pipelines, and GenAI platform engineering
• Experience with distributed systems and streaming/event platforms (e.g., Kafka)
• Experience operating AI/ML systems in a regulated or healthcare environment
• Working knowledge of AI/ML lifecycles, model deployment patterns, and MLflow or equivalent tooling

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.