Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an
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Lead Engineering in San Francisco
15 active opportunities · Updated September 2026
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Explore current lead engineering jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.
About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Within Premium Support, Dedicated Support Engineers combine deep technical troubleshooting with an enduring understanding of our most strategic customers’ architectures, critical workloads, and business priorities. Through proactive reliability work, ownership during incidents, and AI-powered support capabilities, we help customers operate successfully as their use of OpenAI grows. About the Role We’re looking for a senior leader to build and scale our Dedicated Support Engineering function globally. You will define its strategy, build the team, and establish how we deliver technically rigorous, proactive support for customers running some of the most complex and consequential workloads on OpenAI. This role combines organizational leadership, technical judgment, and executive customer engagement. You will establish a model in which DSEs develop deep customer context, independently advance difficult investigations, anticipate operational risks, and drive issues through resolution. You will also turn what the team learns into improvements that benefit customers across OpenAI. You should bring experience building technical organizations that maintain long-term accountability for enterprise customers. Leadership in Technical Account Management, enterprise Support Engineering, or a comparable technical customer function is particularly rel
From $200K/yr
The Datadog for Startups (DDFS) program helps the next generation of fast-scaling companies adopt best-in-class observability and security from day one. We're looking for the technical engine of this program - someone who can sit across from a startup CTO, earn credibility in the first five minutes, and help them see how Datadog fits into their stack before they've even finished describing it. You'll be the first technical member on a lean, five-person team, owning the technical motion end-to-end: discovery calls, demos, startup enablement, forward-deployed engineering projects, and representing Datadog at founder events across San Francisco. This isn't a traditional SE seat - it's part solutions architect, part technical consultant, part startup evangelist, and it requires someone adaptable, proactive, and ready to take initiative without being told what to do next. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Run discovery calls with startup CTOs and engineering leads to identify quick wins, validate technical needs, and position Datadog against alternatives like Grafana, New Relic, Sentry, and Clickhouse Deliver tailored Datadog demos and help startups get instrumented quickly - removing friction, showcasing value, and ensuring smooth technical onboarding, particularly around AI/ML observability, infrastructure scaling, and security Build automation to improve internal team workflows - EX: outreach, reporting, the application process, and website updates Represent Datadog for Startups at accelerator demo days, hackathons, conferences, founder dinners, and workshops across San Francisco Build relationships across SF's startup ecosystem - founders, VCs, accelerator partners, and technical communities - and develop thought leadership content for tech
Datadog's Forward Deployed Engineering function is in an active growth phase, and the FDE Lead will play a central role in shaping what comes next. Working in close partnership with the Head of Datadog for Startups and Forward Deployed Engineers, and the existing FDE team, you will help define and expand the FDE framework, build out the structures and processes that allow the team to operate at scale, and extend the program's reach well beyond any single customer segment. This role sits at the rare intersection of sales, execution, program design, and hands-on engineering leadership. You are part field technical leader, part program architect, and part cross-functional connector. You will help determine what the FDE motion looks like at Datadog, contribute to its playbook, and push the boundaries of what the team can deliver. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Evolve and scale the FDE operating model end to end: engagement intake, scoping, sprint delivery, handoff back to account teams, and the success metrics (time-to-value, adoption lift, ARR influence, NPS) and reporting infrastructure that support them. Build out a catalog of FDE offerings spanning observability quickstarts, custom integration development, LLM/AI observability accelerators, CI/CD pipeline instrumentation, and cost optimization deep dives, and contribute to their pricing and business models, including free-to-paid conversion plays, paid deployment packages, and post-deployment success motions. Capture product and feature gaps uncovered during deployments, translate them into structured prioritized briefs, and partner with PM and Engineering to strengthen the field-feedback channel that informs roadmap decisions on a regular cadence. Hire, onboard, an
Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is seeking an experienced AI Systems Reliability Engineer to help define, build, and maintain the infrastructure and processes that ensure the reliability, scalability, and performance of Postman’s AI-powered API and agentic systems in production. This role focuses on monitoring, availability, incident response, and automation to support AI services and tools trusted by millions of developers globally. What You’ll Do Develop and manage reliability metrics (SLOs) for AI-driven API services and agentic AI platform features Implement comprehensive observability and monitoring systems for real-time performance and fault detection Design and drive automated failover, recovery, and incident response strategies for high-availability AI infrastructure Optimize resource utilization, particularly GPU/accelerator efficiency, ensuring cost-effective AI system operation Collaborate closely with engineering, platform, and product teams to align reliability efforts with broader organizational goals Lead efforts to build internal tooling and automation focused on AI system stability and operational excellence Drive continuo
$240K – $300K/yr
Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders. What you’ll do You will lead the engineering team responsible for Brex’s GTM Engineering surfaces, enabling our growth engine across Marketing, Sales, and self-serve funnels. This role focuses on building and optimizing our marketing website (Brex.com), GTM applications, top-of-funnel experiences, and AI-powered systems that increase efficiency, reduce CAC, and improve sales and marketing effectiveness. Where you’ll work This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and
$240K – $300K/yr
Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders. What you’ll do You will lead an engineering team focused on building the systems and product experiences that power customer activation at Brex, including onboarding, account setup, verifications, and integrations workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys. The ideal candidate is an engineering leader with experience scaling user-facing onboarding system
About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to lead the engineering, characterization, and productionization of flexible and compliant components in robotic platforms. You will partner closely with cross-functional teams to translate material concepts into engineered subsystems that meet functional, durability, and manufacturing requirements. This role focuses on understanding how soft materials behave in dynamic mechanical systems — including fatigue, creep, hysteresis, wear, and environmental degradation — and designing assemblies that perform consistently at scale. You will work with materials such as elastomers, foams, thermoplastic polyurethanes (TPUs), engineered fabrics, knitted and woven textiles, cables, and other flexible load-bearing or transmission elements, integrating them with rigid hardware, sensors, and actuators using fabrication methods such as bonding, molding, lamination, and sewn assemblies. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Design and integrate compliant or flexible materials into mechanical subsystems and rigid hardware interfaces. Leverage FEA tools to characterize material behavior under operational loads, including tension, compression, abrasion, fatigue, and environmental exposure. Develop test methods and validation protocols to evaluate durability, performance, and failure modes of soft components. Collaborate with cross-functional teams to transition early prototypes into manufacturable designs. Source and evaluate materials in collaboratio
About the Team: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction
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. The design team at Plaid is made up of product designers, researchers, and content strategists who work with our cross-functional partners to create Plaid’s products. Please visit https://designedbyplaid.com/ to learn more about the Design team. The Consumer team at Plaid builds and owns the key consumer touchpoints from Plaid: Plaid Link and our future direct to consumer experiences. Plaid Link is the embedded UX that all of Plaid’s customers integrate in order to securely have their end-users share their bank data via Plaid, and Plaid’s core business is built on consumer trust and confidence in that platform. It’s this team’s responsibility to build on the success of the existing platform to keep innovating and delivering high quality consumer experiences that unlock financial freedom for users leveraging Plaid’s products. We're looking for an experienced Product Designer to own the design of Plaid’s consumer experiences. This is novel scope: a first-party, direct-to-consumer product inside a company most people know only through other companies' apps. You'll be the sole designer on a small, senior team, partnering closely with one PM and one engineering lead (as well as a nimble team of IC engine
About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments. The team partners across OpenAI, including Applied Engineering, Research, IT, Security, Infrastructure, and Engineering, to provide secure and scalable platforms for identity, access management, permissioning, orchestration, and safe AI research. About the Role We’re looking for an engineering leader to lead Identity Infrastructure Engineering, the team building the systems that govern and scale access across OpenAI’s research, engineering, and internal platforms. This role sits at the center of cloud infrastructure, identity, software engineering, and security-critical operations. You’ll lead engineers building control planes, policy systems, workload and agent authorization patterns, infrastructure-as-code, and operational foundations that help OpenAI move quickly while keeping access reliable, auditable, least-privileged, and safe under failure. The ideal candidate has led teams responsible for large-scale, mission-critical infrastructure. They can go deep into code and architecture when needed, while giving engineers and technical leads the clarity and ownership to do their best work. They set technical direction, grow strong teams, make durable architecture decisions, and turn ambiguous 0-to-1 problems into platforms OpenAI can trust and build on for years. In this role, you will: Build and lead a high-performing Identity Infrastructure team, going deep enough technically to set direction while empowering the team to own delivery. Define the strategy for identity platform as the policy plane for access across people, agents, workloads, services, clouds, and internal systems. Scale Acc
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . TwoTwenty is Pinterest's innovation lab, building visual-first AI products — assistants, Gen-AI creation tools, and editing experiences — with startup speed at Pinterest scale. We're looking for a Senior Director of Engineering to lead a team of 10 (7 direct reports across ML engineering, software engineering, data science, and product management), own the technical strategy for TwoTwenty's AI product portfolio, and scale the org from scrappy to enduring without losing what makes it fast. This role reports to the VP of Product Management, Core, and partners closely with Pinterest's Core Product & Engineering, Advanced Technologies Group, and Trust & Safety teams to ship AI features that reach hundreds of millions of Pinners. What you'll do: Drive execution of TwoTwenty's 1–3 year technical strategy across visual AI assistants, gen-AI cre
Technical Program Manager – Applied Infrastructure About the Team The Applied team safely brings OpenAI’s technology to the world, powering products like ChatGPT, and the APIs for GPT and more. Behind these products is a complex and rapidly evolving infrastructure platform that enables scale, performance, and safety. The Applied Infrastructure TPM team partners across engineering to lead foundational programs that ensure OpenAI’s infrastructure can meet current and future demand. About the Role We’re looking for a seasoned Technical Program Manager to drive critical infrastructure programs across the Applied organization. This TPM will focus on cross-cutting initiatives such as general compute capacity planning, process transformation, cost and quota attribution and optimization, and coordination across infrastructure and product stakeholders. There will also be focus on evolving OpenAI’s infrastructure to support growth, scale and new products. This work is core to how OpenAI manages and grows its infrastructure footprint in a disciplined, scalable way. Location: San Francisco, CA (Hybrid – 3 days/week in-office) In this role, you will: Serve as the DRI for complex infrastructure programs spanning CPU planning, orchestration, and other resource management domains (e.g. networking, storage). Build and operationalize systems to capture demand signals, model future capacity needs, and align infrastructure planning across internal teams and partners external to the company. Partner closely with Infrastructure, Product and Finance teams to forecast infrastructure usage patterns and ensure supply/demand alignment. Lead cost attribution and quota enforcement programs to promote stability and ensure equitable access to resources across teams. Drive simplification and standardization of infrastructure tooling and processes across Applied and Infra organizations. Drive cross functional programs to evolve our infrastructure to support new growth and scale Work with external v
About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with
About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role Modal's LLM inference platform delivers frontier performance for open-source models with best-in-class elasticity and developer experience, made in part possible by our custom runtime with GPU memory snapshots and multi-cloud substrate . We're looking for a leader to own the direction and execution of this platform to continue to establish us as the clear market leader, working closely with customers like Cognition, Doordash, Ramp, and many more. You'll be leading a group of highly talented engineers working on our market-leading LLM inference offering, spanning the serving stack, routing infrastructure, internal agentic optimization platform, and the user-facing product surface area. This is a hands-on leadership role — expect to split your time between technical contribution, product shaping and people management depending on what the team needs. You'll set direct
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