Systems And Solutions Engineer in United States

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Abuse Research team is dedicated to proactively hunting for emerging abuse vectors and studying complex attacker behaviors. Rather than just reacting to alerts, the team maps complete abuse paths across Stripe products and external systems to validate novel findings and explain the underlying product conditions that enable fraud. By building continuous abuse tests with agentic testing and related systems, they translate their deep research into actionable threat advisories, strategic control recommendations, and regression scenarios that fortify Stripe’s defenses. What you’ll do You will lead the Abuse Research Group (ARG)—a team of threat intelligence analysts, fraud researchers, and detection engineers focused on proactively identifying and mitigating threats to Stripe and our merchants. You will set the research agenda, guiding work across threat actor tracking, hands-on fraud investigations, merchant ecosystem defense, and the detection pipelines that turn findings into production enforcement. You will scale the team through hiring, coaching, and talent development, while serving as a technical advisor on complex investigations. You will also own ARG's relationships with key partners—including Risk, Trust & Safety, Fraud Platform, and Security Engineering. Lead, develop, and retain a team of threat intelligence analysts, fraud researchers, and detection engineers who thrive at the intersection of adversarial research an

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a team focused on building operational capacity for new, ambiguous, and fast-moving areas of work. The team defines what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. About the Role We are seeking a Device Safety & Risk Operations Specialist to build the safety operating model for a new category of consumer hardware. This is a senior individual-contributor role for someone who can turn emerging product risks and incomplete requirements into practical workflows, controls, launch plans, and durable systems. You will define how product-safety incidents, critical escalations, regulated cases, and privacy-sensitive issues should be identified, investigated, escalated, resolved, and learned from. You will also establish operational requirements for case management, data access, decision logging, quality assurance, monitoring, and cross-functional response. You will stand up priority workflows through launch and early operations, then help transition them into durable homes across USRO and partner teams. The right person combines deep operational judgment with strong technical and hardware product fluency. They can move from executive-level risk framing to detailed workflow design, tabletop exercises, launch readiness, frontline guidance, and post-launch improvement. Location / work model: San Francisco, CA; hybrid, 3 days/week in-office. Please note: This role may involve exposure to sensitive or concerning material. Strong discretion, judgment, and resilience are essential. In This Role, You Will:

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i

About the Team The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg

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! Who are we? Cohere is at the forefront of AI innovation, building cutting-edge language models and AI systems. Our Finance team plays a critical role in supporting our rapid growth and ensuring operational excellence. We value technical expertise, collaborative problem-solving, and a commitment to accuracy and compliance. This role offers the opportunity to make a significant impact on our financial infrastructure while working at the intersection of finance and transformative technology. As we scale our business and navigate an evolving financial landscape, you'll play a pivotal role in driving operational excellence and serving as a key partner on accounting implications of major business decisions. In this role, you will: Lead and own the complete month-end close process, ensuring timely and accurate financial reporting across all entities Oversee all audit activities, partnering with external auditors and managing internal control documentation Collaborate on special projects including system implementations, process improvements, and acquisition integration efforts Direct general ledger operations, account reconciliations,

About the Team OpenAI’s Cyber team works to make frontier AI safe, trusted, and transformative for developers and enterprises. This team is building the security foundation for Codex: the native controls that govern what Codex can access and do, and the interfaces that allow customers and security partners to inspect, constrain, approve, and respond to Codex activity. Our goal is to make Codex secure by default, governable by enterprises, and interoperable with the security products customers already trust . This extends the existing product direction around tenant-scoped tools, guarded actions, approval systems, and scalable partner interfaces. About the Role We are looking for a deeply technical Product Manager to help build Codex security controls and the partner ecosystem around them. This role focuses on securing Codex itself : how identity, permissions, tools, MCP servers, repositories, secrets, networks, and high-impact actions are governed across Codex products. You will also help define standard interfaces through which authorized customer and partner systems can provide security context, inspect activity, return policy decisions, receive telemetry, and initiate bounded responses. You will work closely with Codex product and engineering, OpenAI Security and Safety, enterprise customers, and partners across application security, identity, cloud security, data security, infrastructure, and security operations. In this Role you Will Build native security controls for Codex Partner with engineering, design, security, and safety teams to develop controls for: Identity, roles, permissions, and tenant isolation. Access to repositories, files, tools, MCP servers, secrets, networks, and infrastructure. Read, write, execute, and deployment authority. Human and policy-based approvals. Prompt-injection and untrusted-content defenses. Audit trails, provenance, stop conditions, revocation, and rollback. Help establish a graduated authority model in which local, read-only

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a team focused on building operational capacity for new, ambiguous, and fast-moving areas of work. The team defines what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. About the Role We are seeking a Device Safety & Risk Operations Specialist to build the safety operating model for a new category of consumer hardware. This is a senior individual-contributor role for someone who can turn emerging product risks and incomplete requirements into practical workflows, controls, launch plans, and durable systems. You will define how product-safety incidents, critical escalations, regulated cases, and privacy-sensitive issues should be identified, investigated, escalated, resolved, and learned from. You will also establish operational requirements for case management, data access, decision logging, quality assurance, monitoring, and cross-functional response. You will stand up priority workflows through launch and early operations, then help transition them into durable homes across USRO and partner teams. The right person combines deep operational judgment with strong technical and hardware product fluency. They can move from executive-level risk framing to detailed workflow design, tabletop exercises, launch readiness, frontline guidance, and post-launch improvement. Location / work model: San Francisco, CA; hybrid, 3 days/week in-office. Please note: This role may involve exposure to sensitive or concerning material. Strong discretion, judgment, and resilience are essential. In This Role, You Will:

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, Seattle, Washington D.C., Raleigh, London, and Amsterdam. AI and intelligent systems are driving the fifth paradigm shift, following previous technological revolutions like mainframes, personal computers, the internet, and mobile devices. We believe, in the foreseeable future, AI will revolutionize the FinTech industry - from how consumers understand and manage their finances, to how developers build applications and how all companies operate. The fintech industry landscape will undergo a fundamental reshape. Plaid in the FinTech AI Ecosystem Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. We believe consumers should be able to understand and manage their financial life through conversational AI interfaces using natural language. We believe consumers should have peace of mind with a trustworthy consent and authorization manager when agents shop for them. We believe identity verification and financial fraud prevention in AI-powered products should feel seamless and embedded for the end users. The list goes on. The most important AI companies, major fintechs, and customer agent platforms are actively trying to integrate Plaid into AI-powered produ

The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 As Director, CX Operations (Support) at ClickUp, you will own strategy, vision, and execution for the Support Operations function , partnering closely with Support and CX leadership while serving as the operational leader for the systems, automation, planning, quality, and insights that power our Support organization. You will set the operating model and performance standards for Support Operations while owning the AI agent harness and automation layer of our CX operating model. You will shape the rhythm of business for our Support organization and unlock data insights, coach organizational performance, transform internal capabilities, and influence strategic decisions across Support, CX, and cross-functional leadership. You will architect, ship, operate, and iterate on AI-driven workflows that enhance and automate customer intake and response, escalation, full support lifecycle management, quality and customer experience, workflow orchestration, and decision support across Support and CX. You'll use AI tools in your own workflow daily while applying strong judgment to validate outputs, manage risk, and improve the repeatable systems the team uses. About the role AI & Automation Architecture Own and operate the AI agent harness and automation layer of our Support operating model Design, ship, manage, and iterate on AI-driven workflows that enhance and automate customer intake and response, escalation, full support lifecycle management, workflow orchestration, quality, and customer experience across Support and CX Build scalable, multi-step agentic systems that Support and CX leaders rely on for pla

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’s Inference Stack team builds the distributed runtime that powers large-scale LLM inference across our platform. We operate at the intersection of distributed systems, model performance, infrastructure, and developer experience. We enable customers to deploy and operate cutting-edge LLM models with industry-leading performance, scalability, reliability, and ease of use. As a Software Engineer on the Inference Stack team, you’ll work across the stack - from the developer experience customers use to deploy models, the libraries used for features like tool calling and reasoning, all the way down to the systems we use to orchestrate deployments in Kubernetes and route traffic efficiently. This is an ideal role for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users. EXAMPLE INITIATIVES Blog Posts https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES Develop infrastructure and orchestration systems for deploying and managing large-scale distributed LLM inference Work across the stack, from customer-facing features to low-le

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

About the Team: GTM Innovation’s mission is to automate 100% of digital knowledge work for OpenAI's GTM so sellers spend more time directly with customers applying their strategy and judgment. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. The team builds and scales a fleet of virtual coworkers that operate as full-time employees and move increasingly ambitious tasks from the foreground to the background. About the Role We’re looking for a product-minded backend engineer to build the systems behind a new generation of AI coworkers: persistent agents that understand their environment, take on meaningful work, and improve over time. You’ll design and ship the foundational infrastructure that makes these agents effective in production, from durable workflow orchestration to long-running agent loops built on the Codex harness to the context, memory, tools, and permissions model they need to act reliably. You’ll also build rigorous evaluation, observability, and feedback systems that make agent quality measurable and continuously improve how these systems perform. This is a hands-on, high-ownership role at the intersection of agent infrastructure, applied AI, and product engineering. You’ll work directly with go-to-market teams and collaborate across OpenAI’s product and research organizations to turn ambiguous, real-world needs into dependable systems that help OpenAI meet the world at scale. In this role, you will: Build and scale durable agent runtimes, long-running agent loops, and workflow orchestration using the Codex harness and emerging agent infrastructure. Design context and memory systems that ground agents in the information they need while preserving clear access boundaries. Develop rigorous evaluation frameworks, production feedback loops, and observability to measure agent quality and improve it over time. Partner directly

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a strategically-minded, technology-focused, and customer-centric Engineering Manager to lead one of our Infrastructure teams here. You will lead a team responsible for building, operating, and scaling the cloud infrastructure and platform systems that underpin CLEAR’s services, ensuring reliability, performance, and security across our environments. A successful candidate brings strong experience in cloud infrastructure, distributed systems, and operational excellence, along with a solid foundation in software engineering. You are an effective communicator who can lead complex infrastructure initiatives from inception through delivery, and thrive in fast-paced environments. This role requires a focus on building resilient, scalable systems, driving automation, and leading and developing high-performing engineering teams. What you'll do: Hire, develop, and grow engineering talent through coaching, mentorship, performance management, and career development planning Set clear goals and expectations, provide regular feedback, and foster accountability across the team Own and execute the roadmap for cloud infrastructure and platform engineering, and reliability initiatives Design, build, and operate a scalable, secure, and highly available cloud platform infrastructure Drive automation across infrastructure provisioning, deployment, and operations to improve efficiency and reduce manual overhead Establish and enforce best practices for system reliability, observability, incident response, and disaster recovery Partner with eng

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. 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: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb