IC Agentic Engineering Manager - Stargate

About the Team

OpenAI’s Stargate Infrastructure team is building and operating the systems that power next-generation AI workloads at massive scale. This includes deploying and managing clusters, networks, and data center infrastructure across first-party and partner environments. As the scale and complexity of these systems grow, we are investing in agentic systems and intelligent automation to improve how infrastructure is deployed, operated, and debugged. This team focuses on applying AI-driven approaches to real-world infrastructure workflows—enabling faster execution, higher reliability, and scalable operations.

About the Role

We are seeking an IC Agentic Engineering Manager to lead the development and application of agent-based systems for infrastructure delivery and operations within Stargate. This is a player-coach role: you will contribute directly to system design and implementation while leading a small team. You will focus on applying agentic systems to infrastructure workflows such as deployment orchestration, system bring-up, issue triage, debugging, and capacity management. This role is not focused on building general-purpose agent platforms. Instead, it is centered on applying agentic systems to solve concrete infrastructure problems, working closely with hardware, networking, and cluster teams.

Key Responsibilities

• Design and build agent-based systems to support infrastructure deployment and operations
• Identify high-impact opportunities to apply agents across workflows such as:
  • cluster bring-up and deployment readiness
  • incident triage and root cause analysis
  • system validation and health monitoring
  • capacity management and operational decision-making
• Lead a small team while contributing directly as an IC across system design, development, and integration
• Partner with infrastructure, hardware, and networking teams to integrate agentic systems into production workflows
• Develop systems that leverage telemetry, logs, and system signals to enable closed-loop automation
• Define evaluation frameworks to measure system effectiveness, reliability, and operational impact
• Drive iteration from prototype to production, ensuring robustness and scalability

Qualifications

• Strong software engineering background in distributed systems, infrastructure, or platform engineering
• Experience building production automation systems or data-driven operational tooling
• Experience applying AI, ML, or agent-based approaches to real-world systems or workflows
• Ability to operate as a hands-on IC while leading a small team
• Experience working cross-functionally with infrastructure, hardware, or systems teams
• Strong problem-solving skills in complex, ambiguous environments

Preferred Skills

• Experience with LLM-based systems, agents, or autonomous workflows
• Background in infrastructure operations, SRE, or large-scale system deployment
• Experience working on cluster bring-up, debugging, or data center infrastructure systems
• Familiarity with telemetry, monitoring systems, and observability pipelines
• Experience building internal tools or platforms for engineering productivity and operations