Operations Manager in San Francisco

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. About the Role You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit

About the Team The Compute Strategy team works across research, engineering, product, finance, legal, and go-to-market teams to develop the partnerships, infrastructure capacity, and commercial models needed to advance AI infrastructure. About the Role As a member of the Compute Strategy team, you will develop commercial strategies for AI infrastructure partnerships and offerings. You’ll translate technical infrastructure opportunities into partnerships, transactions, and revenue. We’re looking for a commercially minded strategist who combines knowledge of semiconductors and AI infrastructure with strong financial judgment and the ability to execute complex partnerships. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Develop strategies for compute partnerships, vendor access, and infrastructure capacity. Structure and execute transactions with chipmakers, compute providers, and other infrastructure partners. Develop pricing frameworks and business cases for infrastructure-related partnerships. Evaluate partner technologies, strategic fit, commercial terms, and execution risks. Coordinate work across research, engineering, product, finance, legal, and go-to-market teams. Turn partnership learnings into repeatable operating models that can scale. You might thrive in this role if you: Have experience in strategy, corporate development, partnerships, or infrastructure transactions. Understand semiconductors and AI infrastructure. Can evaluate complex technical and commercial opportunities. Bring strong financial, analytical, and strategic judgment. Can influence and align technical and business stakeholders. Have negotiated or executed complex partnerships. Are comfortable operating in a fast-paced environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence ben

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role We are looking for a visionary and execution-oriented AI transformation lead to serve as a high-impact partner for our most strategic Fortune 100 accounts. In this role, you’ll be the architect of change, moving beyond simple software implementation to help the world's largest organizations fundamentally rethink how they work. You’ll sit at the intersection of business strategy and cutting-edge technology, translating the power of the WRITER platform into measurable P&L impact and helping executives navigate the shift to an AI-first operating model. This is a rare opportunity to build the playbook for enterprise AI transformation. You won’t just be managing accounts; you’ll be driving the next industrial revolution by helping C-suite leaders move from AI experimentation to full-scale value realization. Your work will directly influence WRITER's product roadmap and help define how the world’s biggest brands use superintelligence to expand human capacity. Thi

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role We are looking for a visionary and execution-oriented AI transformation lead to serve as a high-impact partner for our most strategic Fortune 100 accounts. In this role, you’ll be the architect of change, moving beyond simple software implementation to help the world's largest organizations fundamentally rethink how they work. You’ll sit at the intersection of business strategy and cutting-edge technology, translating the power of the WRITER platform into measurable P&L impact and helping executives navigate the shift to an AI-first operating model. This is a rare opportunity to build the playbook for enterprise AI transformation. You won’t just be managing accounts; you’ll be driving the next industrial revolution by helping C-suite leaders move from AI experimentation to full-scale value realization. Your work will directly influence WRITER's product roadmap and help define how the world’s biggest brands use superintelligence to expand human capacity. Thi

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role Join WRITER's security team as a staff detection and response engineer and help protect the AI infrastructure that's transforming how the world works. You'll build sophisticated detection systems that identify attacks targeting our AI platform, training data, and model deployments while creating automated response capabilities that scale with our explosive growth. This isn't just traditional security work – you're defending cutting-edge AI/AGI systems against adversaries who are evolving their tactics as fast as AI itself advances. This role combines hands-on security engineering with strategic thinking to stay ahead of novel threats that don't exist in textbooks yet. You'll be the operational arm of our security function, translating threat intelligence into real-time detections, coordinating incident response across multiple teams, and hunting for sophisticated attacks across GPU clusters and distributed training environments. If you're excited by the challen

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! As the Senior Director of Solutions Architecture for the Americas at Cohere, you will own the US and Canada commercial Solutions Architecture function. You will lead the team that turns enterprise interest in agentic AI into deployed, production systems, and you will be accountable for the technical win in the most competitive AI market in the world. The United States and Canada are our largest commercial opportunity, and this seat owns how we win them. You will take an established, distributed team of strong technical people and raise what it can do — setting the bar and establishing the operating rhythm that lets a team of generalists run consistent, industry-fluent plays at enterprise scale. You will set direction for the function, sit on the Solution Architecture leadership team alongside the regional leaders for EMEA and Asia Pacific, and contribute to company-wide decisions with your peers across Sales, Product and Engineering. In this role, you will: Lead and Scale the Organization: Build, coach and develop a high-performing Solutions Architecture organization across the US and Canada, and grow the senior technical talent

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

What you’ll do Execute weekly system-level exploratory testing across the scanner and supporting software; log and triage issues with clear reproduction steps. Work with engineering to debug root cause and validate fixes. Help maintain the DHF and traceability between user needs, design requirements, tests, and results. Own practical test execution logistics (fixtures, test data, environments, calibration artifacts) and keep things repeatable. Help build the continuous testing strategy: automated tests where feasible, plus structured manual and system tests. Support V&V activities, including coordination with external partners as needed. What we’re looking for Strong hands-on testing instincts for complex electromechanical systems with substantial software. Ability to write clear bug reports and communicate risk/impact. Experience building and maintaining test plans/protocols; comfort operating lab equipment and debugging across layers. Useful experience Experience testing complex systems end-to-end (automation where it pays off, plus hands-on hardware/instrumentation). Medical device or other safety-critical environments and comfort translating risk into practical test coverage.

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

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 Security Governance, Risk, and Compliance (GRC) team is part of Plaid’s security organization, focused on enabling the business by proactively managing information security risks and maintaining effective controls. Our mission is to reduce the likelihood and impact of security risks while operating a robust assurance program that builds trust with our customers, consumers, and data partners. We own Plaid’s security compliance frameworks, run our audits and risk programs, and partner across the company to keep Plaid’s platform secure, resilient, and aligned with industry and regulatory expectations. GRC Engineering is how we make all of that scale — turning compliance into code, evidence into telemetry, and audits into a continuous, automated capability. The Role: You will own GRC Engineering at Plaid — a foundational, high-ownership role defining an emerging discipline from the ground up. Today most of our compliance work is manual and point-in-time; you will turn it into an engineered system that is continuous, data-driven, and scalable, and set the technical direction for the field. You will: Define the discipline and the architecture — how GRC Engineering works at Plaid, not just execute with

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

About the Team The Corporate Development team sits at the intersection of OpenAI’s strategy and the global AI ecosystem. Partnering closely with engineering, product, and business leaders, we analyze markets, technologies, and companies to identify opportunities that accelerate OpenAI’s mission and long-term strategy. Bringing together expertise in strategy, M&A, and integration, the team leads the end-to-end process of sourcing, evaluating, negotiating, and integrating acquisitions and other strategic transactions. About the Role The Corporate Development Deal Lead will own high-priority M&A and strategic transaction work from early evaluation through diligence, structuring, negotiation, approval, and close. This person will translate strategic priorities and market insight into actionable deal opportunities, build the business case for transactions, and drive cross-functional alignment with senior stakeholders. This is a hands-on, high-ownership role for someone who can combine strategic judgment, financial rigor, founder relationship-building, and crisp execution. The ideal candidate can lead complex transactions, partner well with executive stakeholders, and help build the AI-native systems, tools, and operating practices that allow Corp Dev to scale. This role is based in our San Francisco HQ. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Lead end-to-end execution of corporate development transactions (e.g., acquisitions and strategic investments), including sourcing, diligence, valuation, structuring, negotiation, and closing. Track and interpret key trends across AI, technology, and adjacent industries, translating the competitive and startup landscape into clear, high-impact insights for OpenAI’s leadership. Proactively source acquisition and other opportunities by building deep relationships across the venture, startup, and incubator ecosystem. Partner closely wi

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're looking for an Optical Interconnect System Engineer to design, qualify, and deploy scalable optical connectivity for large-scale AI infrastructure. This role spans fiber-system architecture, optical-mechanical integration, validation, reliability, deployment, and serviceability. You will work with optical, mechanical, electrical, networking, manufacturing, reliability, and data-center teams to translate system needs into practical interconnect solutions. This is a hands-on role for someone who can connect design decisions with installation, qualification, troubleshooting, and long-term operational performance. In this role, you will: Define optical interconnect architectures and requirements across hardware platforms and rack-level systems. Design high-density fiber systems for performance, density, reliability, installation, and serviceability. Lead optical-mechanical integration and cross-functional design reviews. Develop test and qualification plans for optical components, modules, switching platforms, and integrated systems. Own optical loss budgets, routing guidelines, handling requirements, and serviceability criteria. Support system bring-up, deployment, troubleshooting, failure analysis, and reliability improvement. Create reusable design guidelines, interface requirements, and qualification methods. You might thrive in this role if you have: Core experience Experience desi

About the Team Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work. This opening sits within the Technology vertical inside Enterprise Verticals. The group focuses on repeatable workflows for people at technology companies, beginning with functions such as data and analytics, sales, and design, and carries the shared platform needs—tool integration, permissions, quality measurement, and safe rollout—across those experiences. We work closely with Design, Research, GTM, Security, and platform teams, as well as with customers and design partners. Success means that people can reach a trustworthy first result, understand what the system did, and keep using the workflow—not merely that a prototype exists. About the Role We are looking for a full-stack product engineer who can own ambiguous enterprise workflows end to end: understand a customer problem, shape the product, build across frontend and backend, work through platform dependencies, instrument quality, and learn quickly with design partners. You will build across ChatGPT Work surfaces, services, plugins, connectors, and data or permission boundaries when the experience requires it. You will make quality and rollout observable through evaluations, product and operational signals, and clear fallback or rollback paths. This is a product-engineering role for someone who can move between user problems and system details without losing ownership of either. The strongest candidates will be able to turn specific customer evidence into a generalizable product, explain scope and architecture tradeoffs, and carry a feature from an early prototype through a bounded production rollout. In this role, you will: Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors. Turn customer a