Ai Systems Engineer in San Francisco

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. Team Description: Plaid is evolving into an AI-first company, and Intelligent Tooling sits at the center of that transformation. The Intelligent Tooling team is being built from the ground up, and our mission is to establish the technical foundations, operating model, and internal platforms that embed AI deeply into Plaid’s coding tools, internal systems, and the entire software development lifecycle. When we are successful, engineers across Plaid will delegate lower-leverage work to AI agents, move faster with confidence, and spend more of their time designing and inventing for customers. Intelligent Tooling owns the platforms and systems that make this possible - from AI coding integrations and SDLC agents to the internal tools that power Plaid’s operations. Role Description: As a Staff Software Engineer on the Intelligent Tooling team, you will build and operate internal systems that directly impact how engineers across Plaid do their work, and own the technical direction for major parts of that surface. This is a hands-on role with significant ownership, where success is measured by real adoption, reliability, and improvements to developer experience. You will work on AI-powered tooling, interna

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for an experienced, hands-on support leader to build and run the support and escalation motion for GPT-Rosalind and OpenAI’s life sciences customers. This is both a builder role and a frontline support role. You will work directly with customers, own complex cases, diagnose technical and operational issues, and coordinate cross-functional teams through resolution. You will also create the intake paths, playbooks, knowledge, tooling, and operating mechanisms needed to support life sciences workflows across ChatGPT, Codex, and the OpenAI API. You’ll partner closely with Account Directors, Product, Engineering and Forward Deployed Engineering, Security, Legal, and bioscience subject-matter experts. You will help customers receive coordinated, accurate answers while maintaining clear boundaries between technical support, scientific consultation, product feedback, and roadmap commitments. This role is an opportunity to define how OpenAI supports scientists and life sciences organizations as they adopt increasingly capable AI systems. In this role, you will: Work directly with Rosalind and life sciences customers, taking ownership of complex technical and operational support cases from intake through resolution. Serve as a critical escalation point and final line of defense for complex technical issues, partner

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge As a Senior Staff Software Engineer, you will serve as a technical leader for OneTrust’s AI Governance (AIG) platform, driving the design, scalability, and reliability of systems that enable enterprises to deploy and govern AI and LLM-powered applications responsibly. You will deeply understand how customers build, deploy, and operate AI systems, and translate those needs into secure, compliant, and observable platform capabilities. Your Mission Development Lead the design and development of Java/Python microservices and shared libraries integrating with AI platforms for OneTrust’s AI Governance product. Design, build, and test cloud-native applications deployed on Microsoft Azure using Core Java, REST, and the Spring ecosystem. Lead the architecture and development of reusable AIG reporting and dashboard capabilities that integrate governance data from SQL databases and analytical platforms with runtime observability signals. Design reusable semantic-layer and metric-abstraction capabilities, including dataset contracts, metric defini

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: Are you the person on your team who builds the agent everyone else ends up using? We're looking for an AI Engineer to join our Training Product team and do that at Baseten. You'll build AI-driven product features for the customers training and post-training frontier models on our platform, and you'll raise the ceiling on how Baseten itself uses AI internally, turning manual workflows into agentic ones that make every other team faster. You'll work directly with our research engineers to scope and build products, taking ideas from a research loop that already works internally to something customers can run themselves. This is a hands-on role with real autonomy. You'll pick the problems worth solving, build the harnesses, execution flows, and guardrails that make AI systems reliable, and own the results. If you've been shipping agents and want that to be the job, let's talk. EXAMPLE INITIATIVES: Take a look at these blog posts written by members of our team: Baseten Training: an autoresearch substrate Introducing Baseten Loops Harnesses are everything. Here's how to optimize yours. Building with NVIDIA Nemotron 3 Ultra and LangChain Deep Agents Code on Baseten RESPONSIBILITIES: Build and ship agentic product experiences, including chat-style and assistant-like interfaces, from prototype to GA. Design the harnesses, execution flows, and guardrails that make AI systems reliable in production. Build internal autom

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is seeking an Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI an

About the Team The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins. About the Role We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production-ready integrations. You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go-to-market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post-launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex. This role is based in our San Francisco office. 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: Own the technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and

OpenAI’s charter calls on us to ensure the benefits of AI are distributed broadly and safely. Our Health AI team focuses on expanding access to high-quality medical expertise and aims to set a high standard for deploying AI responsibly in high-stakes domains. Improving health will be one of the defining impacts of AGI. Today, millions of people lack access to reliable medical information, and clinicians around the world face increasing time and resource constraints. We are building AI systems that support patients, clinicians, and health workers, while meeting the highest standards for safety, reliability, and privacy. We are seeking full stack software engineers to help build and scale products used by consumers and care providers globally. You will work closely with product, design, and research teams to ship real systems in a fast-moving, high-impact environment. In this role, you will: Design and build scalable fullstack systems for consumer and enterprise health. Own end-to-end feature development—from early design and implementation through deployment, monitoring, and iteration. Build and maintain data pipelines and services that meet strict privacy, security, and compliance requirements (e.g., HIPAA). Collaborate closely with researchers and safety teams to integrate reliability, evaluation, and guardrails into production systems. Debug, optimize, and harden systems to support high availability, performance, and global scale. Take ownership of ambiguous problems and drive them to practical, high-quality solutions. You might thrive in this role if you: Are deeply motivated by improving health outcomes and expanding access to medical expertise. Are a strong engineer who enjoys building durable, well-designed systems. Have 5+ years of experience writing maintainable, production-quality code. Can operate with high agency—owning problems end-to-end with minimal supervision. Enjoy working in fast-moving, cross-functional teams with engineers, product managers, desi

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely 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 As a Senior Software Engineer on Sentry’s AI/ML team, you’ll be responsible for building the evaluation infrastructure that measures the accuracy, reliability, and real-world performance of our AI systems. This role is critical to ensuring that our debugging agents and AI-powered features behave correctly, safely, and predictably as they scale. You’ll design datasets, benchmarks, and test harnesses that turn ambiguous AI behavior into measurable signals, helping the team ship AI with confidence. In this role you will Design and build robust evaluation frameworks to measure accuracy, reliability, regressions, and edge cases in AI systems Create and curate high-quality datasets, golden test cases, and benchmarks grounded in real production data Build automated test harnesses and metrics pipelines to continuously evaluate models, prompts, and agentic workflows Partner closely with applied AI engineers and product leaders to define what “good” looks like and translate it into measurable criteria Own the evaluation lifecycle for major AI initiatives, from early experimentation through production monitoring You’ll love this job if you Care deeply about correctness, rigor, and measurement in AI systems Enjoy turning fuzzy product goals and model behavior into concrete tests and metrics Like building foundational infrastructure that unlocks faster iteration and higher confidence for the entire AI team Thrive in cross-functional environments and enjoy influencing model design through better evaluation Qualifications Minimum 5+ years of professional experience with a Bachelor’s degree in computer science, machine learni

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

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 We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp

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 As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. In this role you will Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles Own the development of major initiatives in the AI/ML space You'll love this job if you Are driven by impact and enjoy working on high-stakes, high-visibility projects Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members Thrive in cross-functional teams and enjoy building features alongside developers and product teams Qualifications Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field Demonstrated expertise building production-grade agentic systems and tools You are comfortable writing production quality code (we use Python) Expertise with deep learning frameworks (we use PyTorch) Familiarity in deploying machine learning models at scale in production