Infrastructure & Engineering Development Program

About the Role

The GTS Infrastructure and Engineering Development Program is a 12-month, in-person development experience designed to build talent for AI-enabled IT and technology services disciplines. The program includes a three-week onboarding bootcamp followed by an embedment with a Global Technology Services (GTS) team. Associates will work on real projects, guided by mentors and senior technologists. The program concludes with placement into a GTS role and fosters community through its cohort-based structure. The program is structured around an "build to operate" philosophy, focusing on translating business needs into technology outputs, operating and automating services at enterprise scale, and utilizing AI as a default method of work.

Note: Candidates pursuing software engineering or AI/ML engineering careers should apply to Optum's Technology Development Program (TDP).

Associate Focus Areas

Assignments will be determined by business necessity, program needs, and available opportunities. Potential areas of support include:

• AIOps and AI for IT Operations: Building and operating AI agents, applying the AI development lifecycle, prompt engineering, and model evaluation/monitoring.
• Automation, DevOps and Tooling: Focusing on deterministic and agentic automation, CI/CD pipelines, infrastructure as code, and self-service technology services.
• Infrastructure and Cloud Operations: Covering cloud operations foundations, compute, storage, data center operations, infrastructure as code, and automation with Python.
• Site Reliability Engineering, Observability and Resiliency: Focusing on observability, reliability and resiliency patterns, ITSM, CMDB, and database operations.
• Identity, Access and Employee Experience: Including network engineering, identity and access management with MFA, SSO, device registration, and developer productivity.

Key Responsibilities

• Own real project work from day one.
• Translate business needs into technology outputs.
• Operate and automate services at enterprise scale.
• Use AI as the default way of working.

Requirements & Tech Stack

• Currently in final year of obtaining a bachelor's or master's degree from an accredited college/university in Computer Science, Computer Engineering, Software Engineering, Information Technology, Management Information Systems, or another technology-focused discipline.
• Foundational understanding of Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs).
• Demonstrated ability to leverage AI-enabled tools to improve productivity, accelerate learning, and support technical problem-solving.
• Foundational understanding of one or more of the following: cloud platforms, networking, infrastructure, or systems administration.
• Working knowledge of at least one scripting or programming language used in technology operations (Example: Python, PowerShell, Bash, Java, C#, JavaScript).
• Demonstrated problem-solving and analytical thinking.
• Demonstrated collaboration and teamwork.
• Demonstrated adaptability and learning agility.
• Demonstrated curiosity.
• Must be eligible to work in the United States without company sponsorship, now or in the future, for employment-based work authorization.

Preferred Qualifications

• Exposure to cloud technologies (AWS, Azure, and/or GCP), containers, and Kubernetes.
• Familiarity with infrastructure as code, CI/CD pipelines, and source code control systems (i.e. Git, GitHub).
• Coursework, certification, home lab, or project experience in networking, systems administration, or site reliability engineering.
• Exposure to observability, monitoring, ITSM, or IT service management tooling.
• Data literacy and analytics skills, including the ability to work with operational data and build straightforward reporting or dashboards.
• Demonstrated capability to:
• Apply AI-enabled tools and automation to reduce manual effort in IT and technology operations.
• Build effective prompts and use AI-enabled tools to investigate issues, summarize technical information, and generate insights.
• Integrate AI into operational workflows such as reporting, dashboards, monitoring, and service processes.
• Collaborate with teams to identify opportunities where technology and AI can improve processes or user experiences.
• Basic familiarity with responsible, compliant, and secure use of AI tools.
• Understanding of Agile frameworks, methodologies, roles, and tools (Kanban, Scrum, SAFe, LeSS, etc.).
• Involvement in additional technical activities (technology clubs, hackathons, home lab, side projects, GitHub, etc.) and/or technology-related employment experience.