Technical Services Engineer Representative 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. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Delivery Engineer Team As a member of the Delivery Engineer team, you will own the post-sales onboarding and data health for customers. Your goal will be to drive data trust, help embed Mixpanel into our customers’ data stack, and deliver on emerging AI integrations — delivering on the full value of Mixpanel as a self-serve analytics platform. You will work and consult with GTM team members and a diverse array of customers to successfully roll out product analytics to their organization and execute on technical projects and services that delight our customers. About the Role As a Delivery Engineer II, you will be on the front lines with our clients as they integrate Mixpanel into their core product development processes. You will lay the foundation for customers to adopt product analytics and get value from Mixpanel by delivering a world-class, on-time, and value-oriented onboarding experience. With your comprehensive project management knowledge, consultative approach, expertise in the analytics space, and technical knowledge of the modern data stack, you will lead our clients' first experience with Mixpanel as they incorporate product analytics into their data ecosystem as a foundational element. With your deep technical breadth and expertise in the analytics space, you’ll be the expert consultant on all things data and ecosystem. As Mixpanel and our customers continue to iterate on agentic integrations, you’ll own ensuring customers are able to build, assemble context, and integrate AI workflows with Mixpanel. Responsibilities Own onboarding and data health for our strategic and high-value c

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. Plaid Support ensures our customers' applications can help their consumers live their best financial lives by ensuring our products continue to operate as expected. We investigate the root cause of integration issues, quantify their scope and impact, and when we can’t fix them ourselves, we work with our Growth and Engineering teams to reach a solution. As we continue to grow, we’re looking for Technical Support Engineers (TSEs) to join the team to help us balance the needs of customers, users and internal stakeholders, while navigating critical technical issues. In this role, you will manage issues from their first symptom to their eventual resolution, communicating with our customers and internal stakeholders throughout the process. People who succeed in this role tend to be empathetic, collaborative, technically minded, and most importantly - customer-centric. They have an interest in learning more about financial services, and are excited to help customers resolve complex issues. TSEs work closely with Plaid’s product and engineering teams, and we have a high technical bar to ensure that we all speak the same language. Our Support team sets aggressive goals to meet the standards our customers ex

About the Team Customer education helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively. The team focuses on role- and skill-based learning paths, practical content, and product experiences that accelerate learning in the workplace. It brings together learning and enablement expertise, field insight, product signals, and measurement to improve learner and business outcomes. Together, these experiences will help enterprise users build practical AI skills, apply them with confidence in their work, and demonstrate what they can do. Employers will gain a clearer view of workforce skills and progress, helping them recognize capability, focus development where it matters most, and build confidence in workforce readiness. About the Role We’re looking for a full-stack engineer to define and build a new class of learning experiences. This is an early-stage product area where technical judgment, product sense, and learner empathy are critical. You will be setting a technical vision for how people use AI to learn how to use AI, safely and beneficially. This is a hands-on, 0-1 product engineering role with broad technical and product ownership. You’ll set direction, make foundational decisions, and ship the first versions of experiences that can grow into the default way people learn at work. You will drive full-stack product experiences end to end, from prototype through launch, instrumentation, iteration, and production hardening. The work spans interaction design, frontend implementation, backend APIs and services, learner state, content and runtime integration, telemetry, evaluation, reliability, safety, accessibility, and launch readiness. You’ll work closely with our education, GTM, and engineering teams to translate how people learn into products people want to use. bring role- and skill-based learning paths into the product, designing coaching, feedback, and adaptive support which responds to each lea

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

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

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role As a Forward Deployed Engineer on Notion’s Services team, you will lead the hands on technical delivery of our most complex customer engagements. You will design, build, and deploy production ready solutions that help enterprise customers integrate Notion as the operating layer for their business. You’ll embed with enterprise customers to design and build solutions that integrate Notion deeply into their technical and operational environments. This includes writing and maintaining custom code, designing and deploying production-grade custom agents and AI workflows with MCP, Agent APIs, and Notion’s automation and execution infrastructure, building data pipelines and resolving complex challenges around scale, permissions, and governance. You’ll embed with enterprise customers to design and build solutions that integrate Notion deeply into their technical and operational environments. This is a customer-facing engineering role for someone who is comfortable writing code, debugging technical issues, explaining tradeoffs to stakeholders, and turning ambiguous customer problems into scalable technical solutions. Your work w

About the Team Security is foundational to OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security organization protects OpenAI’s technology, people, and products by building and operating deeply technical systems that must work reliably at massive scale. Our work underpins OpenAI’s commitments around safety, privacy, and security across research, products, and emerging platforms. The Host Assurance team exists to make bare metal and VMs dependable & scalable foundations for OpenAI: secure by default, verifiable in practice, and resilient across providers and operating models. We operate at the trust boundary between hardware and cloud-scale orchestration, ensuring that hosts are eligible to safely run workloads with predictable security properties and auditability. About the Role OpenAI is seeking a Software Engineer, Host Assurance to build and operate the services, APIs, and host software that establish and maintain trust in our compute infrastructure. You will own production software from design and implementation through testing, rollout, observability, and operation. Your work will support capabilities such as machine identity, certificate issuance and enrollment, secure bootstrap, and host attestation across bare-metal and VM environments. Success in this role requires strong technical judgment, the ability to reason across software and host-system boundaries and learn unfamiliar parts of the stack, and a practical mindset for building systems that are secure, reliable, and usable in fast-moving production environments. The systems you build will sit on the critical path of OpenAI’s frontier infrastructure investments and will directly shape how large amounts of compute are brought online - securely, responsibly, and at global scale - underpinning long-lived commitments around privacy, security, and reliability. You will partner closely with infrastructure, research, and confidential computing initiatives—inc

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

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 mission of the Developer Relations team is to empower developers to easily use and understand Plaid’s products, delivering a supportive, industry-leading developer experience via scalable, broad-reaching methods. The scope of this role covers all of Plaid's commercially available, customer-facing products. We’re looking for an experienced Developer Relations Engineer to help the world’s fintech companies (and we believe every company is a fintech company, even if they don't know it yet) integrate with Plaid's APIs. In this role, you’ll create best-in-class developer experiences, cementing Plaid's reputation as the most trustworthy, developer-friendly financial services API. This is a highly technical, highly visible role with direct impact on Plaid’s product, brand, and developer experience. Responsibilities Create and evolve developer documentation for Plaid’s APIs – writing new content, and improving clarity, accuracy, and usability of existing content. Distill complex technical topics into approachable, accurate explanations for a broad developer audience. Design and build sample applications, demos, and tutorial videos that demonstrate the benefits of integrating with Plaid’s APIs and the be

About the Team The Infrastructure Engineering function sits within IT and is responsible for reliably building, deploying, and operating critical on prem and hybrid environments that power internal services and critical R&D environments. This is an early, high-leverage technical role focused on applying strong Site Reliability Engineering discipline to environments where uptime, safety, recoverability, and security are non-negotiable. This person helps replace bespoke, one-off infrastructure with standardized infrastructure-as-code building blocks that compound reliability and operational leverage as OpenAI scales. About the Role We are looking for an experienced Site Reliability Engineer working on security infrastructure to design, build, and operate reliable, secure, and scalable infrastructure that underpins identity, access, endpoint, and shared platform services across the company. In this role, you will be a senior technical owner for infrastructure and identity systems end to end, from architecture and implementation through policy enforcement, upgrades, recovery, and day-two operations. You will build durable, production-grade platforms that remove operational friction, enforce security by default, and enable teams to move faster with confidence. This role is well suited for a hands-on senior engineer who thrives in ambiguity, enjoys owning complex systems end to end, and raises the reliability and security bar by replacing fragile implementations with standardized, repeatable infrastructure. This role is based in our San Francisco HQ and requires in-office presence. In this role, you will: Design, build, and operate reliable infrastructure across on-prem, hybrid, shared, and product adjacent environments. Establish standardized infrastructure patterns that replace bespoke implementations with repeatable, auditable, secure-by-default systems. Own the lifecycle of critical infrastructure platforms, including provisioning, deployment, upgrades, patching,

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. 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: Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data Analyze requirements and deliver end-to-end solutions that address

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

About the Team The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: Design eval pipelines that are reliable, reproducible, and extendable Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

About the Team OpenAI Consumer Devices is building the next generation of products that bring powerful AI into people’s everyday lives. Guided by OpenAI’s mission to ensure AGI benefits all of humanity, our team combines world-class researchers, engineers, designers, and operators who care deeply about creating useful, intuitive, and responsible technology. You’ll have the opportunity to work alongside exceptional people on ambitious, zero-to-one challenges at the intersection of hardware, software, and AI. This is a chance to help define an entirely new category of products—and shape how people experience AI in the future. The Systems Integration team is critical in this mission, turning complex hardware-software development into reliable product signals. We validate complete device experiences across software, cloud services, connectivity, accessories, and real-world operating environments, combining hands-on system testing, structured test development, hardware-in-the-loop environments, diagnostics, and automation to uncover issues that component-level testing alone cannot reveal. About the Role As a Systems Test Engineer, End-to-End Validation , you will design and execute end-to-end testing for complex device experiences spanning hardware, software, connectivity, cloud services, and accessories. You’ll translate product behavior and real-world use cases into structured, reproducible test procedures and build test environments that allow failures to be reliably reproduced and diagnosed. You’ll also identify opportunities to automate repetitive or high-value scenarios, working with engineers to turn complex manual workflows into scalable validation systems. Because this is a new category of devices, you’ll have the opportunity to build the end-to-end validation foundation early—shaping test coverage, environments, and workflows from prototype through launch. We’re looking for someone who combines strong systems thinking, hands-on testing skills, technical curiosi