AI Operations Engineer

About the Team & Role

The Corporate Engineering team is building and scaling the next generation of enterprise AI infrastructure at Robinhood. Our mission is to make AI capabilities reliable, secure, and accessible across the company, enabling teams to build, deploy, and operate intelligent solutions at scale.

As an AI Operations Engineer, you'll support, maintain, and improve the AI platforms and infrastructure used across Robinhood. You'll work hands-on with LLM integrations, automation, monitoring, and production systems, partnering with engineers and internal users to troubleshoot issues and build solutions that make AI capabilities more reliable and easier to use.

This role is based in our Menlo Park, CA, New York, NY, and Bellevue, WA offices, with in-person attendance expected at least 3 days per week.

Responsibilities

• Build internal tooling, automation, and self-service solutions that streamline AI operations, reduce manual intervention, and improve developer experience.
• Support and maintain enterprise AI platforms and infrastructure across cloud-based and on-premises environments.
• Troubleshoot technical issues involving LLM integrations, APIs, model behavior, and system performance with developers and internal teams.
• Support enterprise LLM integrations (including Anthropic Claude and Google Gemini), monitoring API usage, token consumption, performance, and reliability.
• Implement and maintain monitoring, observability, and deployment workflows for AI systems.
• Collaborate with Product, Software Engineering, Business Systems, and AI Strategy teams to resolve recurring issues and improve enterprise AI solutions.

Qualifications

• Experience in IT Operations, Site Reliability Engineering, or AI infrastructure and support, operating complex production systems.
• Practical experience working with AI platforms, LLM integrations, or AI-powered applications (such as Anthropic Claude, Google Gemini, or similar models).
• Working knowledge of Linux administration and experience writing scripts or automation using Python, Bash, or similar languages.
• Familiarity with infrastructure management, configuration, or orchestration tools such as Terraform, Ansible, Chef, or Kubernetes.
• Experience troubleshooting production systems and working with monitoring or observability tools.
• Strong problem-solving skills, curiosity, and interest in emerging AI technologies.
• Ability to communicate technical issues clearly and collaborate across teams.

Bonus

• Exposure to GPU infrastructure, AI workload orchestration, vector databases, RAG applications, agentic frameworks, or hybrid cloud environments.