[Remote] Lead SWE, AI Dev/IT Operations - Remote or Hybrid in DC or MN

Note: The job is a remote job and is open to candidates in USA. Optum is seeking a Lead Software Engineer to build and operationalize AI, machine learning, and automation capabilities for IT Operations. The role focuses on predictive analytics, incident response, self-healing infrastructure, and production AI workflows in collaboration with engineering, operations, and data science teams.

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

• 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
• Hands-on experience contributing to agentic or autonomous AI systems in operational contexts
• Experience in healthcare, regulated industries, or large-scale enterprise platforms
• Experience working in agile, product-driven environments delivering scalable, high-impact solutions
• Working knowledge of IT operations concepts, including incident management, CMDB, monitoring, alerting, and reliability engineering
• Familiarity with Responsible AI and governance frameworks, including fairness, transparency, and explainability
• Solid technical communication skills, including the ability to explain AI concepts to non-technical stakeholders

Benefits

• Remote work from anywhere within the U.S.; for hires in the Minneapolis or Washington, D.C. area, work in the office a minimum of four days per week is required.
• A comprehensive benefits package, subject to eligibility requirements.
• Incentive and recognition programs, subject to eligibility requirements.
• Equity stock purchase, subject to eligibility requirements.
• 401k contribution, subject to eligibility requirements.

Company Overview

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