Tech Lead, Deployment & Operations — Custom Infrastructure

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

About the Team OpenAI’s Legal team helps advance our mission by tackling novel legal issues in AI. Our team brings together professionals across technology, privacy, intellectual property, corporate, employment, tax, regulatory, and litigation. Our regulatory compliance work turns legal requirements into practical programs that support responsible AI development and deployment. About the Role As a Legal Program Manager focused on regulatory compliance, you will build and manage cross-functional programs that translate counsel’s guidance into practical, sustainable operations. Your initial focus may include content moderation and/or frontier AI governance, with the mix shaped by team priorities and your strengths. You will partner with internal and external counsel, other legal program managers, and technical and business teams to coordinate implementation, evidence collection, reporting, and ongoing compliance. You’ll build repeatable systems that scale across regulations, products, and jurisdictions, helping teams navigate emerging requirements with clarity and sound judgment. This full-time role is based in San Francisco, CA, or New York, NY. In this role, you will: Lead regulatory compliance programs end to end: define scope, owners, milestones, dependencies, risks, and escalation paths, and drive execution with counsel and cross-functional partners. Translate counsel’s regulatory guidance into repeatable workflows, controls, and documentation. Depending on your portfolio, this may include content moderation disclosures, transparency reporting, reporting and appeals workflows, or frontier AI model launch readiness, evaluation and risk-management evidence, and incident reporting. Build strong partnerships across Product, Engineering, User Operations, Governance, Risk and Compliance (GRC), Global Affairs, Communications, and Go-to-Market to align program priorities and deliverables. Support regulatory inquiries, audits and investigations with counsel, organizing ev

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team The People Operations team owns the systems, processes, and programs that make the employee lifecycle run — from day one through every transition in between. We believe that clean data, simple workflows, and well-designed technology are what let the rest of the People & Talent function do its best work. About the Role We're looking for a People Operations Manager who can look at a messy, ambiguous problem and turn it into a clear plan — then execute it. Day-to-day, you'll own our HR technology stack, lead process transformation across the employee lifecycle, and serve as the go-to partner for Payroll, IT, Legal, and the broader People & Talent team when something needs to be built, fixed, or rethought. You'll work directly with vendors, HRBPs, and leadership to make sure our operations are scalable, compliant, and actually simple to use. In the first year, success means moving us from where we are to where we should be: better-configured systems, documented processes, and a team that trusts what's in our tools. Responsibilities Lead HR operations programs end-to-end — define scope, owners, milestones, risks, and success measures, often starting from an undefined brief. Serve as the primary functional owner for core People technology platforms (e.g., HRIS, ATS, LMS, performance tools), including configuration, upgrades, and feature evaluation. Lead technology deployments, platform conversions, and module rollouts, coordinating across IT, HRIS, and vendor teams. Research and benchmark HR technology trends to build and maintain a People tech roadmap that supports scale. Apply AI and e

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,