Senior System Architect in United States

About the Team The Real Estate & Workplace (REW) team creates and operates the workplaces and services that help OpenAI employees do their best work. Within Workplace Experience, Transportation connects our global office network through programs designed around employee needs, local conditions, and operational excellence. About the Role As Global Transportation Program Sr. Manager, you will own the strategy, expansion, and day-to-day performance of OpenAI’s employee transportation programs. You will make it easier for employees to get to and between our workplaces through reliable, accessible, and cost-effective commuting options. We’re looking for a builder who has launched and scaled employee transportation programs across countries in a fast-growing organization. You will translate our global workplace expansion plans into a transportation roadmap, establishing the systems, vendor partnerships, and operating practices needed to support new markets and growing offices. You’ll balance global consistency with local needs, creating repeatable approaches that enable local teams to deliver reliable service as the company scales. Location and work model : San Francisco, CA based, with required travel up to 10% to our global offices. This role will be in office Monday - Wednesday, with the option to work from home Thursdays and Fridays. In this role, you will: Own a global transportation expansion roadmap aligned with office openings, headcount growth, and changing commute demand. Prioritize investments, forecast capacity and costs, and lead launches from market assessment through operational readiness and ongoing service delivery. Manage the global employee transportation portfolio across shuttles, parking, micromobility, transit and commuter benefits, and EV charging. Determine the right service mix for each market based on employee needs, local infrastructure, accessibility, and cost. Build a scalable operating model across regions, including repeatable launch pla

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 Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An Overview of this role We are seeking a Staff Product Manager to serve as an internal PM embedded within this team. This is not a traditional external-facing product role—it is an internal platform product leadership position. You will own the roadmap for our enterprise systems, act as the strategic voice of the business within engineering, and bring senior product craft to a team of Analysts and engineers who build and operate GitLab's revenue infrastructure. This role is ideal for a seasoned product leader who has deep Quote-to-Cash or Finance domain knowledge, thrives at the intersection of business strategy and techni

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Site Reliability Engineers keep GitLab's user-facing services and production systems running reliably at scale. They combine software engineering with operational excellence, applying sound engineering principles, automation, and continuous improvement to build, operate, and evolve our production infrastructure. This is a single application for Site Reliability Engineering opportunities across our Infrastructure Platforms department. Rather than asking you to choose the right team or level upfront, we evaluate your skills holistically and match you to the opportunity that best aligns with your experience

About the Team The Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. This role is based in San Francisco, CA. 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’ll: Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safet

About the team ​​Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. In this role, you will: Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model util

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 (Summer 2026 AI Internship - Applications Open Now) We're seeking an AI Engineer Intern to work alongside our AI team on large-scale AI and Agentic systems from data pipeline to production deployment. This role is scoped for someone with foundational experience who wants to deepen it: you'll own discrete pieces of real systems under the mentorship of senior engineers, not shadow work or isolated coursework-style projects. What You'll Do You’ll work directly with the AI team, taking responsibility for well-scoped pieces of real systems, with mentorship from senior engineers. Benchmarks & Evaluation Contribute to APIFlow-Bench , our open-source benchmark for real API-development work: design and review benchmark tasks and their mock API environments, extend the evaluation harness and task-generation pipeline in Python, and help maintain the public multi-model leaderboard with statistical confidence intervals. Help build a new action-level AI safety benchmark: instead of grading what a model says, it scores what an agent actually does inside a simulated enterprise API environment. You’ll work on scenari

What you’ll do Be the generalist EE for the scanner system: integration, bring-up, debugging, and making the electrical side of the device reliable and serviceable. Own ultrasound experimentations that feeds the image reconstruction team Design and execute experiment setups for transducer characterization (element sensitivity, bandwidth, cross-talk mapping, beam profile measurements) and ex vivo / phantom clinical testing. Acquire, process, and analyze RF and baseband signals for data quality assessment and benchmarking. Design simple boards and adapters as needed (monitoring, power/safety, interface/conditioning), and take them from prototype through a stable revision. Prototype quickly, then harden what works: wiring/harnessing, grounding, safety interlocks, and reliable integration across subsystems. Own practical test setups and documentation (fixtures, scripts, procedures) that make experiments repeatable and results comparable over time. What we’re looking for Strong hands-on EE background with experience building, debugging, and iterating on real systems in the lab. Solid understanding of signal processing fundamentals — knows what to measure, how to condition and digitize it, and how to evaluate signal quality in the context of an imaging system (SNR, bandwidth, dynamic range, artifacts). Comfortable spanning system integration + occasional design work (schematics/layout reviews or light PCB design) in a fast-moving environment. Ability to work at the boundary between hardware and algorithms: measure reality, communicate constraints, and help close gaps vs simulation. High agency and practicality: able to set up experiments, get trustworthy data, and unblock others on a lean team. Useful experience Analog/mixed-signal, or high-speed data capture experience; strong instincts for instrumentation and noise/debugging. Ultrasound or acoustic sensor handling: hydrophone calibration and field mapping, transducer impedance characterization, element-level sensitivity

About the Team Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for the most severe user-safety risks—including Frontier Risk and Material Harm—that are accurate, fast, defensible, and scalable. The Cyber vertical turns policy into reviewer standards, calibrated judgment, quality systems, escalation paths, and safe automation. About the Role We’re looking for a senior cybersecurity and cyber intelligence practitioner who is also an operations leader, strategist, and people manager. You’ll bring sound cyber judgment, strong analytical and automation instincts, and the ability to stay close to the work while setting direction, managing and developing people, aligning partners, building programs from 0→1, and translating ambiguity into durable operating systems. This role combines senior individual-contributor depth with direct people-management accountability. You’ll personally shape complex cyber judgments, operating models, SOPs, quality systems, and automation strategies while building, coaching, and holding accountable a high-performing team. You’ll also lead through influence across FTEs, BPO partners, and cross-functional teams. Baseline operational health—including quality, queue coverage, productivity, and SLA adherence—is table stakes; success is additionally measured by durable improvements to decision quality, stakeholder alignment, reviewer capability, and the systems that run the operation. This role is based in San Francisco, CA. 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: Set the strategic direction for Cyber Operations and translate high-level organizational priorities into a clear operating model, roadmaps, SOPs, escalation paths, quality goals, and safe-access strategies. Serve as the senior cybersecurity and cyber intelligence expert for complex and high-risk decisions across ChatGPT, API, Codex, agents, and

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Grow your career while continuing Exact Sciences’ inspiring work. Changing roles within the company allows you to develop your skills while changing the future of cancer in a new way. Schedule - Monday - Friday 8 am -4:30/5 PST Position Overview This role is responsible for diagnosing and resolving failures in enterprise laboratory instruments and automation systems, conducting root cause investigations, and escalating service issues to minimize downtime. It includes performing routine preventive maintenance and calibrations to ensure equipment reliability and compliance with service standards. The position requires accurate documentation aligned with Good Documentation Practices (GDP) and regulatory requirements such as OSHA, FDA, ISO, and CLIA. Success in this role involves developing technical expertise, training others, and collaborating across teams and vendors to support troubleshooting and project execution. Flexibility, commitment to quality, and a focus on process improvement—including SOP development and workflow optimization—are essential. Key Accountabilities: Include, but are not limited to, the following: Troubleshooting & Repair: Under general supervision, diagnose, repair, and resolve failures following established procedures on instrumentation and automation systems within the laboratory by applying technical expertise to restore functionality. Escalate unresolved or complex issues to senior s

What you'll do Run human-subjects recording sessions end-to-end: participant prep and fitting, sensor configuration and calibration, stimulus delivery, real-time signal monitoring, and session documentation. Own daily system QC for a one-of-a-kind sensing instrument: baseline noise recordings, per-sensor health checks, log review, and escalation of anomalies before they touch a dataset. Own participant operations: recruitment coordination, scheduling, screening, consent, and compliant handling of participant records. Stand up and maintain the operational backbone of the program: SOPs for acquisition, QC, and participant workflows — documentation that survives you. Handle first-pass data operations: file conversion, organization, metadata, and quality review in Python. Partner daily with the program lead to refine acquisition protocols and improve system performance over time. What we're looking for Hands-on experience acquiring physiological or imaging data from human participants in a clinical or research setting Obsessive consistency and attention to detail: you notice when something is off and you don't let it slide. Professional, patient, and calm with research participants — sessions succeed or fail on how people feel in the room. Basic scripting ability (Python and/or shell) for QC and data-handling tasks, or clear aptitude and motivation to build it. High ownership of the unglamorous parts: scheduling, documentation, tidy data hygiene. Discretion — parts of this program are not yet public. We'll walk you through the specifics, including the exact technology you'd be operating, in the first conversation. Useful experience Controlled or low-noise recording environments and highly sensitive instrumentation. Physiological signal-processing tools in Python. Human-subjects research administration (IRB protocols, consent workflows). Research studies involving structured tasks or sensory protocols with human participants.

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Who We Are: Every day, tens of millions of people from around the world come to Roblox to play, learn, work, and socialize in immersive digital experiences created by the community. Our vision is to build a platform that enables shared experiences among billions of users. This is what’s known as the metaverse: a persistent space where anyone can do just about anything they can imagine, from anywhere in the world and on any device. Join us and you’ll usher in a new category of human interaction while solving exceptional challenges that you won’t find anywhere else. What You’ll Do: Robux is Roblox’s Virtual Currency: it’s how Users buy virtual items and how Creators earn a living. The Economy Platform team is the owner for all systems powering Robux transactions and has the goal of maintaining Roblox’s Economy healthy and vibrant. As a Principal Software Engineer for Virtual Economy Platform, you will be responsible for improving and scaling Roblox core monetization systems. You will report to Virtual Economy’s Senior Engineering Manager. The scope of Economy’s team includes the several Purchasing, Pricing and Payout systems. Those systems enable developers to monetize their game

ABOUT THE TEAM Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. The Cyber vertical turns policy into reviewer standards, calibrated judgment, quality systems, escalation paths, and automation guardrails. ABOUT THE ROLE We are looking for a senior cybersecurity practitioner and operations strategist to raise the quality, scalability, and technical rigor of our Cyber Operations. You will combine hands-on cyber judgment with systems-level operating design: resolve the hardest dual-use questions, evolve SOPs, uplift reviewers and vendors, and build practical tools and automations. This is a senior IC role. Success is not primarily cases closed; it is durable improvement in the operating model and the reviewers who run it. IN THIS ROLE, YOU WILL: Drive the Cyber Operations operating model across domain priorities, SOPs, escalation paths, quality health, vendor capability, roadmap inputs and help inform trusted access strategies. Serve as the senior cyber expert for complex or high-risk decisions across ChatGPT, API, Codex, agents, and emerging product surfaces. Translate policy ambiguity, quality misses, appeals, and reviewer disagreement into clear decision rules, calibration examples, training, and tooling requirements. Build durable operating systems and quality loops: golden sets, holdouts, double-labeling, adjudication, error taxonomies, reviewer calibration, and automation evaluations. Raise FTE and BPO capability through onboarding, certification, coaching, recurring calibration, and vendor-performance partnership. Use quality, appeals, SLA, backlog, and disagreement signals to diagnose root causes and prioritize high-leverage fixes. Build hands-on solutions—SQL analyses, scripts, dashboards, LLM eval workflows, evidence enrichment, routing logic, and lightweight automations—that improve decision quality and reduce manua