Senior Software Engineer II - AI Azure Cloud Engineer

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

• Cloud & Platform Engineering

• Design, implement, and manage enterprise-scale Azure cloud solutions
• Lead Infrastructure as Code implementations using Terraform
• Build and manage CI/CD pipelines using GitHub Actions and Azure DevOps
• Architect and support Azure Databricks environments and data platforms
• Design cloud networking, security, governance, monitoring, and cost optimization frameworks

• Manage Kubernetes platforms and containerized workloads

• AI & Generative AI Solutions

• Design and build AI-powered applications, bots, and virtual assistants
• Develop and deploy AI Agents using Microsoft Copilot Studio, Azure AI Services, Azure OpenAI, or similar platforms
• Implement Retrieval Augmented Generation (RAG) architectures using enterprise knowledge sources
• Build intelligent workflow automation solutions leveraging Generative AI
• Integrate Large Language Models (LLMs) into enterprise applications

• Develop AI-powered self-service and operational support platforms

• AI-Driven Optimization & Automation

• Identify opportunities where AI can improve operational efficiency, reliability, and user experience

• Implement AI-based solutions for:

• Infrastructure optimization
• Cost optimization
• Incident prediction and remediation
• Capacity planning
• Operational intelligence
• Security and compliance monitoring
• Release quality validation

• Drive AI adoption across engineering and business functions

• Leadership & Innovation

• Provide technical leadership for AI and cloud modernization initiatives
• Mentor engineering teams on AI engineering best practices
• Partner with business and technology stakeholders to identify AI transformation opportunities

• Stay current with emerging AI technologies and industry trends

• Works with less structured, more complex issues
• Serves as a resource to others
• 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

• 10+ years of overall IT experience
• 5+ years of Azure Cloud experience

• Solid expertise in:

• Azure Platform Services
• Azure Databricks
• Terraform
• GitHub Actions
• CI/CD
• Kubernetes
• Networking
• Monitoring & Observability
• Experience designing enterprise-scale cloud architectures
• Experience implementing Infrastructure as Code and GitOps practices

• Solid scripting skills using Python, PowerShell, or Bash

• AI Skills:

• Hands-on experience building AI solutions in enterprise environments

• Experience developing AI bots, virtual assistants, or intelligent agents

• Experience with:

• Azure OpenAI
• Azure AI Services
• Microsoft Copilot Studio
• Prompt Engineering
• RAG implementations
• Vector databases and semantic search
• LLM integration patterns
• Understanding of AI governance, responsible AI, and security considerations
• Experience implementing AI-driven automation and optimization solutions

Preferred Qualifications

• Experience building enterprise knowledge assistants
• Experience with Agentic AI frameworks
• Experience implementing AI solutions for DevOps, Cloud Operations, and Data Engineering
• Experience with MLOps and AI deployment pipelines

Key Technologies

• Cloud & DevOps
• Azure
• Azure Databricks
• Terraform
• GitHub Actions
• Azure DevOps
• Kubernetes
• Docker
• Networking
• Monitoring
• AI & GenAI
• Azure OpenAI
• Copilot S…