Answer Engine Optimization Lead in United States

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable 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: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

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’re looking for signal integrity (SI) system design engineers who have a deep expertise in the SI area, and hold strong system level design knowledge 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: Lead system signal integrity (SI) design for AI supercomputer product in the data center application. Collaborate with chip, package, boards, rack and system engineers, design partners to drive system SI design and develop innovative interconnect and high-speed technologies Identify and evaluate new technologies and methodologies to improve signal and power integrity in product design, and contribute to the development of new products and technology by providing expertise in signal integrity Perform simulation and modeling to identify and troubleshoot signal integrity issues Lead system interconnect design, bring up and qualification As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. You might thrive in this role if you: Have at least 10 years of industry experience, including experience design hardware system and SerDes testing for data center applications Have a strong bias toward action, and won’t take no for an answer. Have experience and good knowledge of system design experience in the SI areas, from chip, SerDes, board, rack level Have ex

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. About the Role We are seeking Performance Modeling Engineers to develop and apply modeling tools that evaluate AI system performance and inform architectural decisions. In this role, you will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI infrastructure. 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. Key Responsibilities Develop and maintain performance modeling tools and frameworks. Build models to evaluate system behavior across: compute, memory, and interconnect subsystems distributed system scaling and bottlenecks. Run simulations and analytical models to support architectural tradeoff analysis. Collaborate with performance modeling lead and system architects to answer forward-looking design questions. Analyze and interpret modeling outputs, translating results into actionable insights. Validate models against real system measurements and workload behavior. Contribute to improving modeling fidelity, usability, and scalability. Qualifications Strong software engineeri

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is building AI BI: a new way for anyone in a company to ask questions and get accurate, auditable answers from their data, whether as visualizations or plain-language insights. We are looking for a senior+ level full-stack engineer to help build this experience end to end. This is not about recreating every long-tail feature from legacy BI tools. We are building something lightweight, composable, and understandable by AI. The goal is to help business users, analysts, and data teams move from question to answer faster, while creating a product that is robust, scalable, and delightful to use. You should be excited to work across the stack, move quickly, and make strong product and engineering tradeoffs. The ideal candidate has experience building durable systems at enterprise scale, but is also comfortable operating with startup speed and ambiguity. In this role, you will Build core product capabilities for AI-native dashboards and analytics experiences using JavaScript (React), Go, Java. Drive projects end to end across frontend, backend, architecture, and product details. Partner closely with product, design, and sister teams to deliver cohesive user experiences. Make thoughtful tradeoffs between speed, quality, and long-term maintainability. Help shape technical

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is building AI BI: a new way for anyone in a company to ask questions and get accurate, auditable answers from their data, whether as visualizations or plain-language insights. We are looking for a senior+ level full-stack engineer to help build this experience end to end. This is not about recreating every long-tail feature from legacy BI tools. We are building something lightweight, composable, and understandable by AI. The goal is to help business users, analysts, and data teams move from question to answer faster, while creating a product that is robust, scalable, and delightful to use. You should be excited to work across the stack, move quickly, and make strong product and engineering tradeoffs. The ideal candidate has experience building durable systems at enterprise scale, but is also comfortable operating with startup speed and ambiguity. In this role, you will Build core product capabilities for AI-native dashboards and analytics experiences using JavaScript (React), Go, Java. Drive projects end to end across frontend, backend, architecture, and product details. Partner closely with product, design, and sister teams to deliver cohesive user experiences. Make thoughtful tradeoffs between speed, quality, and long-term maintainability. Help shape technical

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog makes products self-driving . It's the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Desktop , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change wh

Define the physical limits of what a chip can do, then break them! NVIDIA's Silicon Co-Design Group sits at the crossroads of architecture, silicon, systems, and manufacturing, where first principles thinking translates directly into product outcomes at scale. As GPU power density and thermal limits approach physical boundaries, the gap between system architecture needs and manufacturable, testable capabilities widens with every generation, and this role exists to close it. You wouldn't be maintaining existing solutions, you'd be identifying where physical constraints will erode NVIDIA's competitive edge before anyone else sees it coming, then building the cross-domain responses that ensure the next generation leapfrogs those limits entirely. The problems here don't have known answers yet: Every generation of NVIDIA silicon pushes closer to the limits of physics. The Co-Design Architect role isn't about optimizing within known bounds; it's about redrawing those bounds entirely. If you want your work to shape what's physically possible in the world's most demanding computing products, this is where that work happens. What you'll be doing: Power, Thermal & Packaging Limits Analysis: Gather and analyze the hard constraints of packaging, power delivery, and thermal dissipation against roadmap demands, predicting when those constraints will reduce competitiveness and acting before they do. Cross-Domain Solution Development: Develop solutions that span silicon features, packaging innovation, firmware and hardware co-design, and DFX updates, ensuring future products are not only performant but testable to the highest quality and reliability standards. Packaging Technology Evaluation: Assess emerging packaging technologies for their voltage/frequency, noise, reliability, and testability implications, determining which are worth adopting an

About the Team The ChatGPT Search Product Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the product infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world. Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration. The team partners closely with: Post-Training on model launches, experimentation, and prompt optimization Search product verticals on new user experiences Inference on GPU efficiencies Indexing and Retrieval on the systems that identify and deliver relevant information Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs About the Role We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Product Infrastructure. You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform. A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing invol

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

Datadog SQL (DDSQL) and Sheets are two of the newest products within Graphing, Datadog’s most-used product area. Together, they give customers flexible ways to query, combine, analyze, visualize, and share data across Datadog. This role owns the product direction and user experience for both products. Your goal is to help users move from raw data to trustworthy answers quickly—whether they prefer writing SQL, working in a spreadsheet, or building visual analyses. Doing this well requires more than adding analytical features. Real-world analysis involves nuanced decisions about data models, joins, aggregations, time windows, missing data, query performance, and the transition from exploration to reusable work. You’ll work closely with design and engineering to make these capabilities understandable without limiting their analytical power. You’ll also help expand the data customers can analyze in Datadog, including third-party and business data alongside operational telemetry. This will make DDSQL and Sheets central analytical tools for a broader range of questions and users. What you'll do: Own DDSQL and Sheets end to end: roadmap, adoption, and growth strategy Partner closely with design to establish a high bar for information architecture, interaction design, and visual polish across complex analytical workflows Use product analytics and customer research to identify friction, improve onboarding, and measure whether users are reaching useful answers faster Define the experience for querying, transforming, visualizing, and sharing data, from query composition and results exploration to errors, performance feedback, and collaboration Define and execute the strategy for bringing third-party data into Datadog: from market research and use-case definition through pricing Expand Datadog SQL from a standalone editor into a platform-wide query capability on all graphs Redesign how users discover and get started with Graphing products: rethink list pages, build onboa