Lead AI/ML Engineer for IT Ops & Automation (Remote)

UnitedHealth Group; Minnetonka (MN); Hybrid; Confidential; Full time

Benefits offered by this job

Comprehensive benefits package

Equity stock purchase program

401(k) contribution

Job summary

UnitedHealth Group's Optum Tech is seeking a Lead Software Engineer to design, build, and operationalize AI/ML capabilities for IT operations. You will develop predictive analytics, intelligent automation, and agentic AI to improve observability and self-healing infrastructure at scale.

You will collaborate with data scientists, engineers, and security teams, delivering production-grade ML models, CI/CD pipelines, and cloud-native solutions across the enterprise.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
• 3+ years of experience building and deploying AI/ML solutions in production environments.
• 3+ years of experience in Python and SQL, with hands-on experience using distributed data processing frameworks such as Spark.
• 2+ years of experience applying ML to IT operations, infrastructure, reliability engineering, or observability domains.
• 2+ years of experience with cloud platforms (Azure, AWS, or GCP), including hybrid and cloud native architectures.
• 2+ years of experience with MLOps practices, CI/CD pipelines, model monitoring, and lifecycle management.
• 1+ years of experience with NLP, Large Language Models (LLMs), Generative AI, and modern AI frameworks.
• 1+ years of experience with containerization and orchestration technologies such as Docker and Kubernetes.

Responsibilities

• AI/ML Development: Design, build, and maintain machine learning models and AI-driven automation for IT operations use cases, including predictive analytics, intelligent automation, and support for autonomous remediation.
• Data & Platform Engineering: Build and maintain data pipelines that ingest structured and unstructured data from observability and ITSM platforms (e.g., Splunk, Dynatrace, ServiceNow, logs, metrics, traces)
• Feature Engineering & Model Support: Develop and maintain feature sets that support anomaly detection, predictive alerting, capacity forecasting, and operational intelligence use cases
• Model Operationalization: Partner with data scientists and platform teams to deploy and productionize ML models, and help ensure they perform reliably at scale
• AI-Driven Automation: Integrate ML and AI outputs into orchestration and automation platforms (e.g., Jenkins, Interlink) to support closed-loop, self-healing operational workflows
• Agentic AI Development: Build components of agentic AI solutions that reason, plan, and execute actions across IT operations, including incident triage, root cause analysis, and resolution
• MLOps Practices: Follow established MLOps standards, model lifecycle practices, and data governance requirements aligned with enterprise security, privacy, and compliance policies
• Cloud & Infrastructure: Use cloud native and hybrid architectures to support real-time analytics, scalable model inference, and resilient AI platforms
• Cross-Functional Collaboration: Work with engineering, operations, security, and business stakeholders to understand requirements, document your work, and contribute reusable patterns for AI-driven operations
• Responsible AI: Apply ethical AI principles, including fairness, transparency, explainability, and accountability, throughout the development lifecycle

Skills

Python

SQL

Spark

NLP

LLMs

Docker

Kubernetes

Cloud platforms

MLOps

Education

Bachelor's degree in Computer Science or related field

Tools

Splunk

Dynatrace

ServiceNow

Jenkins

Interlink

Job description

UnitedHealth Group's Optum Tech is seeking a Lead Software Engineer to design, build, and operationalize AI/ML capabilities for IT operations. You will develop predictive analytics, intelligent automation, and agentic AI to improve observability and self-healing infrastructure at scale.

You will collaborate with data scientists, engineers, and security teams, delivering production-grade ML models, CI/CD pipelines, and cloud-native solutions across the enterprise.