Product Lead in United States

About the Team OpenAI is a frontier AI research and deployment company. Frontier research is at the center of how we advance our mission, with researchers, engineers, product leaders, operators, and many other teams working together to turn new capabilities into systems that benefit humanity. The People team helps OpenAI attract, engage, and support the exceptional talent this work requires. Employer Brand sits at the intersection of Research, Recruiting, Communications, Marketing, and Brand. Its mandate is to continue to establish OpenAI in the talent market as the unique and leading frontier research lab—not simply another technology company—and make our distinctive research environment, mission, culture, and opportunity for impact relevant and tangible to every priority talent audience. About the Role We’re hiring an Employer Brand Manager to build and scale the strategy, narrative, and operating system that shape how priority talent understands OpenAI. This senior individual contributor will anchor our employer brand in OpenAI’s identity as a frontier research lab and translate an evidence-backed “why OpenAI / why now” narrative into campaigns, researcher and employee stories, recruiter and hiring manager enablement, and candidate experiences. This role is especially important as OpenAI competes for exceptional talent across research, engineering, product, and other mission-critical functions in a fast-moving field where external perceptions can be incomplete or change quickly. You will develop a clear, credible talent narrative for priority audiences—anchored in frontier research and substantiated by individual agency, world-class infrastructure, research-to-product translation, deployment scale, and a willingness to answer hard questions candidly. This role is responsible for ensuring the external brand resembles our culture and ethos internally, therefore must remain immersed in various OpenAI research and applied branches. This role is based in San Francisco

About the Role OpenAI's ads business is scaling quickly. As the Data Scientist for Ads Demand, you will build the measurement and insight foundation for understanding demand health and advertiser value across the marketplace. You will partner closely with Ads Sales leadership and Ads Product leadership—along with Marketing Science and product and sales teams—to diagnose advertiser performance, define benchmarks, identify growth opportunities, and turn advertiser feedback into product priorities. Your work will shape demand strategy, improve advertiser outcomes, and help OpenAI build for its most valuable advertisers. What You'll Do Demand Health & Measurement Define the North Star metrics, diagnostic framework, and measurement strategy for demand health across the ads system. Build the operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix; identify emerging risks and opportunities. Diagnose changes in demand through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for Sales and Product leadership. Advertiser Performance & Benchmarks Own the end-to-end view of advertiser outcomes—including delivery, ROAS, conversion performance, retention, and budget efficiency—for individual advertisers and key cohorts. Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption, with statistically sound peer comparisons. Develop early-warning signals and opportunity scoring that help sales teams surface under-delivery, performance risk, and advertiser growth potential. Set standards for metric definitions, data quality, and interpretation so leaders can separate real marketplace changes from seasonality, selection effects, and measurement artifacts. Insights, Adoption & Advertiser Feedback Partner with Marketing Science, Sales, and Product to translate analysis into credible advertiser-fac

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Senior Medical Director, Clinical Informatics Position Summary The Senior Medical Director for Clinical Informatics and Healthcare Delivery (HCD) Technology Product serves as the senior physician leader across healthcare delivery technical domains, providing clinical insight and technical expertise to drive end-to-end technology execution and ensure that Epic-enabled solutions advance core business outcomes. This role is the clinical expert and trusted physician advisor for teams across HCD technology, driving effective enterprise governance, improving clinician experience, enhancing patient outcomes, and supporting organizational strategic priorities. The Senior Medical Director will also serve as the product leader for two core HCD technology domains - Center Operations and Quality/Stars. The Senior Medical Director brings hands-on clinical and Epic build expertise, partners closely with operational and technical leadership across the enterprise to align the Epic roadmap with organizational strategy, has excellent clinical judgement and keeps patient experience, safety, and outcomes at the center of everything we do, and represents the clinical voice in enterprise governance, escalation, and innovation efforts. Key Responsibilities Clinical Product & Technology Leadership Serve as the senior product leader across Clinic Operations and Quality

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. Our Go-to-Market team helps organizations understand, adopt, and deploy OpenAI’s technology to solve meaningful business challenges and create lasting value. The Technology team works with leading software, internet, cloud, infrastructure, cybersecurity, semiconductor, and digital-native companies as they build new AI-powered products, transform internal operations, and rethink how they serve their customers. We partner with executives, product leaders, engineers, and go-to-market teams to help organizations integrate OpenAI’s capabilities into their products and businesses responsibly and at scale. The team collaborates closely with Solutions Engineering, Customer Success, Product, Research, Partnerships, Marketing, and Operations to turn customer priorities into successful, durable deployments. About the Role We are looking for an experienced Account Director, Tech to help build and grow OpenAI’s business across the technology industry. You will own relationships with a portfolio of strategic technology companies, helping executive, product, and technical leaders understand how OpenAI’s products can accelerate innovation, improve productivity, and create differentiated customer experiences. You will be responsible for developing account strategies, creating qualified pipeline, navigating complex enterprise sales cycles, and expanding adoption across products, teams, and use cases. This role requires a combination of enterprise sales leadership, technical fluency, commercial judgment, and the ability to operate credibly with both business and engineering stakeholders. You should be comfortable engaging with customers that have sophisticated technical environments, rapidly evolving AI strategies, and high expectations for product performance, security, reliability, and scale. Success in this role will be measured by revenue growth, depth of customer adoption,

About the Team The Search research team focuses on building the systems that help AI systems find, retrieve, and use information from the world. We aim to make answers more useful and grounded for more than a billion ChatGPT users. About the Role We’re looking for a Technical Program Manager to lead a broad portfolio of research and engineering programs that power search. You’ll partner closely with researchers, engineers, and product leaders to turn ambitious goals into clear plans, resolve dependencies, and move complex technical work forward. This role combines technical depth, product judgment, and hands-on execution. You’ll work across retrieval, indexing, and model improvements, while collaborating with policy, legal, and external data partners. You’ll help teams make informed tradeoffs and build practical ways of working that support a fast-moving research environment. This role is based in San Francisco, CA. In this role, you will: Lead programs across model training, retrieval, large-scale indexing, and search infrastructure. Translate evolving goals into prioritized workstreams with clear owners, milestones, dependencies, and resource needs. Partner with research, engineering, and product leads to define requirements and make tradeoffs across scope, quality, performance, timelines, and cost. Establish program success metrics and use them to guide priorities and track improvements in coverage, answer quality, responsiveness, and trust. Identify technical and cross-functional risks early, drive blockers to resolution, and communicate progress and decisions clearly to teams and leadership. Coordinate with product, policy, legal, and external partners on data access, use, and presentation, helping teams resolve decisions that span technical and non-technical domains. Manage dependencies with data providers and build repeatable processes that help research and engineering teams execute effectively as the search effort grows. You might thrive in this role if you

About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. Own the quality and impact of the team’s work across solution design, implementation, production readiness, adop

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. ABOUT THE TEAM: We exist to improve Product leaders’ understanding and decision-making on how to profitably grow the business. Our North Star is to increase workload contribution margin dollars above the current forecast by serving as an objective, full-stack business partner. We do this by measuring key metrics, inferring actionable insights, catalyzing strategic decisions, and accelerating operational efficiency across Product, Engineering, and Sales. ABOUT THE ROLE: This is a high-visibility role that sits at the intersection of product strategy and financial analysis, giving you a unique vantage point to influence how we scale our business. We aren't looking for someone to just execute tasks and pull data; we need a partner who can navigate ambiguity, drive workstreams, and anticipate the next steps. This role is best for proactive problem-solvers with business intuition and a high level of curiosity. You will work on critical projects and collaborate with executives to turn complex data into decisive action. WHAT YOU WILL DO: Develop & Maintain Financial Models: Build and iterate on financial models that track both revenue and cost drivers, enabling accurate forecasting and real-time visibility into workload contribution margins. Drive Revenue & Margin Insights

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’s Product team builds the network that powers open finance. At Supplier Products, we focus on building trusted, transparent experiences for financial institutions operating in Plaid’s ecosystem. Responsibilities: You will lead a team of 6 engineers, ranging from mid-level to Staff, developing them through clear goal setting, coaching, and feedback. You’ll define and drive the long-term strategy for this focus area, in close partnership with technical and product leaders across Plaid. You’ll collaborate with cross-functional partners to identify high-leverage opportunities, shape the roadmap, and dive deep into technical design and execution details to ensure consistent delivery of high-impact business outcomes. You’ll uphold a high bar for technical quality and delivery velocity, leading by example. Qualifications: 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management. 1+ years of engineering management experience Deep experience designing scalable, reliable architectures that support real-world products at scale. Track record of building and growing high performing engineering teams (either as an engineer or a manager). Our mission

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments. Preferred Qualifications: Currently pursuing a PhD in computer science, machine learning, or a related field. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas. Experience developing and evaluating large-scale models or machine learning systems. Familiari

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Datadog is looking for a driven, entrepreneurial Customer Marketing Manager to join our Corporate Marketing team — a group of talented professionals responsible for sourcing, creating, and amplifying stories of customers who are achieving meaningful technology and business outcomes with Datadog. This role is designed for marketers who thrive in dynamic environments, are passionate about building genuine customer relationships, and know how to turn great stories into compelling, data-driven programs. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Source and track opportunities to promote customer wins by working with cross-functional partners across product marketing, partner marketing, sales, customer success, marketing operations, demand generation, and more Track and report on program performance, including participation rates, customer reception, content output, and influenced pipeline and closed deals Build a portfolio of customer advocates through online and in-person engagements to source strong stories and promotional opportunities Interview customers and product leaders — in-person and on camera — to produce customer marketing assets, like case studies, video testimonials, promotional quotes, and slides Design, deliver, and continuously optimize programs and incentive strategies that attract customers to participate in advocacy activities Lead programs that drive high-quality customer reviews to peer review sites such as Gartner Peer Insights, G2, and TrustRadius Influence how the broader team operates by modeling best practices, championing process improvements, and driving adoption of AI tools and cross-team efficiencies Who You Are: You have 4+ years of experience in customer marketing and/or advocacy for a B2B technology company

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You'll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You'll own durability and cost at petabyte scale, from streaming and batch replication between origins, to garbage collecti

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. Responsibilities: Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality Building and maintaining automated pipelines that will enforce the correctness of code examp