Lead Software Engineer Data Platform Manager Consultant in San Francisco

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. What you'll do Grow and develop a team of engineers with high expectations for ownership and impact Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities fo

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 the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for a Delivery Director, Capacity programs for our on-premises data center builds and neo cloud (GPU cloud) delivery programs. This is a high-visibility, execution-critical role sitting at the intersection of infrastructure engineering, capacity planning, vendor/partner management, and customer delivery. You will own the end-to-end delivery lifecycle for large-scale compute infrastructure — from initial site/capacity commitments through power, networking, and hardware bring-up, to production-ready GPU/compute capacity landing in the hands of internal teams or customers. You'll be the person who turns ambitious infrastructure roadmaps into predictable, on-time, delivery. RESPONSIBILITIES Own delivery of on-prem infrastructure builds — colocation expansions, power/cooling readiness, rack-and-stack, network fabric bring-up, and hardware acceptance testing — coordinating across colo providers and partners, network engineering, hardware ops, and vendor teams. Drive neo cloud delivery programs — manage capacity delivery from GPU cloud and neo cloud partners (e.g., colocation/bare-metal/GPU cloud providers), including contract milestones, capacity ramps, SLAs, and go-live readiness. Build and maintain master delivery schedules across concurrent, multi-site, multi-vendor programs, integrating power/shell timelines, hardware lead times, logistics, and software/platform readiness into a single critical path.

About the Team The People Technology team builds and operates the systems that support how OpenAI hires, develops, and supports its people. The team brings together People Systems and People Innovation Labs, a product engineering group focused on rethinking how we find and retain exceptional talent and help employees do their best work. People Systems owns the company’s core people-technology ecosystem, including platforms such as Workday and Ashby. People Innovation Labs builds new employee and People Team experiences on top of that foundation, including OpenHouse, our internal employee hub, and AI-powered products and automations. Together, we are working toward a model in which our enterprise systems provide reliable data, controls, and core business logic, while employees and managers can complete more of their work through simple, integrated, and AI-native experiences. About the Role We are looking for a People Systems Lead to manage the People Systems team and shape how our core systems evolve. You will be responsible for the reliability and effectiveness of our current environment while helping us move beyond the constraints of traditional enterprise software. This includes stabilizing and improving platforms such as Workday and Ashby, designing the integrations that connect them to the broader technology ecosystem, and partnering with People Innovation Labs to surface workflows through OpenHouse, Slack, and AI-powered experiences. This role requires someone who is comfortable moving between strategy, technical design, and team leadership. You should understand People systems deeply, be able to work through integration and architecture decisions with engineers, and translate complex organizational needs into scalable solutions. You will also manage vendor relationships, develop the People Systems team, and drive alignment across People, Engineering, Finance, Security, Legal, and other partners. This role could be a fit for someone who has grown up in People S

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 Data Governance team makes sure Plaid handles consumer and customer data responsibly — and can prove it. Our mission is to enforce Plaid's privacy commitments and regulatory obligations in the systems themselves rather than in policy documents: we build the platform and controls that govern how data flows through Plaid — where it lives, who can use it, for what purpose, and for how long. That includes verifiable deletion of consumer data on request, enforcement of data-use restrictions so downstream systems can only use data in permitted ways, and the cataloging and classification that let Plaid know what data it holds and how sensitive it is. We operate at the scale of Plaid's entire data footprint, and correctness and auditability matter to us as much as throughput. As a Staff Software Engineer on Data Governance, you will set the technical direction for how Plaid enforces data governance at scale. You'll lead the design of distributed backend systems that reliably delete, restrict, and track data across dozens of services, making architectural decisions whose blast radius spans the whole company. You'll drive multi-quarter initiatives from ambiguous privacy and regulatory requirements through

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 . We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love. What you’ll do: Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling Work with internal customers on critical business use cases that rely on big data Provide thought leadership to the entire company on how data should be

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

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 Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

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 The mission of the Monetization team is to establish our product-led packaging, subscription model, and billing and scale them as we expand and grow our business. Our team is responsible for building robust Billing systems, focusing on payments, renewals, sales tax, and revenue. We also work closely with all the teams to integrate their products with our packaging model thus offering our customers the best features, pricing, and services through self-serve purchases and our Sales channels. We’re looking for an experienced Senior Engineer who will lead our initiatives for a powerful config-driven platform, improving customer purchase experience and working on the internal tools to match the scale of the growth of Postman. What You'll Do Work on our core Monetization platform to improve offer management, including packaging, plans and pricing, which support the pre-purchase workflow and on our Billing platform to improve data capture for revenue recognition and ARR reporting. Lead the active development of our internal services to introduce new frameworks, optimize the APIs, and improve scale and reliability. Contribu

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu