Senior AI Operations Engineer, Enterprise Tech

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. 

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. From enterprise LLM integrations to agentic workflows and hybrid cloud infrastructure, we're creating the foundation that supports how Robinhood leverages AI internally.

As a Senior AI Operations Engineer, Enterprise Tech, you'll play a key role in building, operating, and improving the infrastructure behind Robinhood's enterprise AI capabilities. You'll work across AI platforms, LLM integrations, automation, and production infrastructure, serving as a technical expert for complex challenges while partnering directly with developers and internal teams. This is an opportunity to help shape a growing function, solve emerging problems in AI operations, and build the systems and tooling that enable AI adoption across Robinhood.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

• →Build internal tooling, automation, and self-service solutions that streamline AI operations, reduce manual intervention, and improve the developer experience.
• →Own complex technical troubleshooting and escalations across AI platforms, working directly with developers and internal teams to resolve issues involving LLM integrations, model behavior, APIs, and system performance.
• →Manage and optimize enterprise integrations with LLM providers, including Anthropic Claude and Google Gemini, focusing on performance, token utilization, reliability, and cost efficiency.
• →Develop and improve observability, monitoring, and deployment pipelines for AI workloads, tracking metrics such as inference latency, API costs, token usage, and error rates.
• →Support and optimize agentic workflows, orchestration layers, vector databases, and retrieval-augmented generation (RAG) systems to improve reliability and scalability.
• →Partner with Product, Software Engineering, Business Systems, and AI Strategy teams to identify recurring issues, incorporate user feedback, and drive long-term improvements to enterprise AI capabilities.

• 5+ years of experience in IT Operations, Site Reliability Engineering, or AI infrastructure and support, with a track record of operating complex production systems.
• Hands-on experience with enterprise AI platforms and LLM integrations, particularly Anthropic Claude and Google Gemini, including API integrations, prompt operations, and token management.
• Strong Linux administration skills and proficiency in scripting and automation using Python, Bash, or similar languages.
• Experience with infrastructure provisioning, configuration management, and orchestration tools such as Terraform, Ansible, Chef, or Kubernetes.
• Strong understanding of production infrastructure, system reliability, monitoring, and troubleshooting across cloud or on-premises environments.
• Ability to independently investigate ambiguous technical problems, identify root causes, and develop scalable solutions that prevent recurring issues.
• Strong communication and collaboration skills, with experience partnering directly with developers and cross-functional teams to resolve technical challenges.
• Bonus: Experience with GPU clusters, AI workload orchestration (Slurm, Ray), vector databases (Pinecone, Milvus), AI frameworks (LangChain, LlamaIndex), or hybrid cloud and bare-metal infrastructure.