Product Design Ai Products Manager in United States

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? The Data Infrastructure team at Cohere is responsible for the storage and data movement layer underlying every model training run. We're building the unified storage layer that feeds our training workloads. It needs to serve petabytes of training data and model checkpoints fast enough to keep thousands of GPUs busy across several training clusters. In this role, you’d have an opportunity to build this system from the ground up. You’d be a key contributor, working on a problem few teams have had to solve at this scale. In this role, you will: Design, build, and operate the distributed storage system that feeds model training and evaluation. Run this system multiple on Kubernetes clusters at petabyte scale. Work with researchers and training-infra teams on how jobs actually read and write data, and turn that into throughput, latency, and durability requirements Work through the networking, I/O, and consistency problems of moving large datasets and checkpoints across regions and backends, with GPU idle time and time-to-insight as the measures of success You may be a good fit if you have: Strong storage fundamentals,

About the Role As a Field CTO (Strategic Pursuits) , you will serve as a strategic bridge between our customers, go-to-market (GTM) teams, and product organization. You will partner closely with Sales, Technical Success, and Product to shape high-impact deals, guide customer architecture decisions, and influence our product roadmap based on real-world adoption and feedback. This is a highly cross-functional, externally facing leadership role for someone who combines deep technical expertise with strong business acumen and customer empathy. In this role, you will: Customer & Deal Strategy Partner with Sales, Product and Technical Success teams to support complex, high-value deals as a technical and strategic advisor. Translate customer business needs into scalable technical solutions and architectures. Engage with senior customer stakeholders (CTO/CIO/VP-level) to drive alignment on vision, roadmap, and adoption. Lead technical strategy discussions during key deal stages, including discovery, solution design, and executive presentations. Architecture & Implementation Guidance Guide customers on best practices for deploying and scaling AI-driven solutions in production. Provide architectural oversight across use cases such as LLM applications, integrations, data pipelines, and security. Act as a trusted advisor to ensure long-term success, not just short-term wins. Product & Feedback Loop Bring structured customer insights back to Product and Engineering teams to inform roadmap and prioritization. Identify gaps, opportunities, and emerging patterns from customer deployments. Influence product direction based on real-world usage, scalability needs, and enterprise requirements. GTM Strategy & Thought Leadership Help shape GTM strategies by identifying repeatable patterns across industries and customer segments. Develop scalable frameworks, reference architectures, and playbooks for broader field teams. Represent the company externally through customer en

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

Become a part of our caring community Humana is seeking a self-driven and collaborative Lead Engineer to join our Interactive Voice Response (IVR) team. In this role, you will deliver innovative IVR solutions and develop robust omnichannel APIs for our enterprise platforms. You will have the opportunity to drive the success of a high-impact, customer-facing application within a Fortune 50 company, working closely with multiple teams throughout the software development lifecycle (SDLC). Lead Engineer –Omnichannel Humana is seeking a self-driven and collaborative Lead Engineer to join our Omnichannel team. In this role, you will design, develop, secure, and enhance enterprise APIs that support high-impact, member facing, applications across Humana's digital and voice channels. This role offers the opportunity to modernize and strengthen existing API capabilities while helping deliver resilient, scalable, and secure omnichannel solutions within a Fortune 50 organization. Key Responsibilities Design, develop, and maintain scalable Omnichannel APIs that support enterprise applications and customer-facing capabilities. Enhance the security, resiliency, performance, and reliability of existing APIs through modernization, improved architecture, observability, testing, and operational controls. Apply AI and AI-assisted engineering practices to accelerate development, improve quality, automate testing, enhance documentation, and identify opportunities for optimization. Partner with architecture, security, cloud, product, engineering, and operations teams to deliver secure, resilient, and enterprise-aligned API solutions. Collaborate with agile teams to plan, track, and deliver API enhancements, platform improvements, and cloud-based capabilities. Develop proofs of

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Join our FDE team and work directly with some of the world's largest organizations to turn their most ambitious ideas into production applications on Replit. As a Forward Deployed Engineer, you'll partner closely with customers to understand their technical and business needs, architect solutions, and build the integrations and applications required to deploy Replit successfully within complex enterprise environments. This is a deeply technical and hands-on role. You won’t just advise customers on what to build—you’ll build alongside them. You’ll take applications from initial idea and prototype through deployment and production, navigate complex enterprise environments, and solve the technical challenges that emerge when AI-powered software development meets real-world infrastructure, data, security, and organizational constraints. You will: Build with Customers: Embed with strategic enterprise customers to design and build high-impact applications and AI-powered workflows on Replit, taking projects from initial concept through production deployment. Architect Enterprise Solutions: Design secure, scalable architectures that connect Replit with customers’ existing systems, data, APIs, identity providers, and infrastructure. Integrate with the customer's stack: SSO, data warehouses, internal APIs, and SaaS systems. Own Technical Deployments: Serve as the technical owner for complex enterprise implementations, identifying blockers, debugging issues, and driving projects through to successful production adoption. Bridge Customers and Product: Develop a deep understanding of how enterprises use Replit and translate field insights, technical constraints, and recurring customer needs into actionable feedback

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We’re searching for a highly motivated, technical leader to design, drive, and operationalize rack-scale factory and deployment flows for next-generation data center products. The ideal candidate will combine deep systems expertise, decisive technical leadership, and a passion for building reliable, debuggable, and scalable manufacturing and deployment solutions. What you’ll be doing: Lead and drive rack-scale/L11 flows for factory and initial data center deployment. Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations. Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp. Champion reliability, debuggability an

About Us: Blockworks is an information platform that sits at the center of the crypto industry. We transform raw, complex data and facts into actionable research, trusted alpha-driven insights, and world-class events. The result is transparency and confidence. Blockworks connects investors and businesses in onchain capital markets. We give businesses a platform to earn trust and provide investors with the information they need to underwrite the asset class. I'm hiring a salesperson. Blockworks builds trust in onchain markets. Data, disclosures, investor relations, APIs, ratings, asset monitoring. You'll sell all of it, often in the same proposal, to the largest protocols, institutions, and enterprises entering crypto. Deals run $100K to $500K+, usually with several stakeholders and very little instructions. You'll be a good fit if you: were top of the leaderboard at a tier one sales org believe deals die on Zoom would rather fly to a maybe than email a yes have run a nine-stakeholder deal with no champion have handed a lead to a teammate because they'd win it faster know the difference between pipeline and hope rebuilt a proposal at midnight because procurement moved the goalposts have spent a Friday night on a deal that wasn't yours have flown to the client for a 45-min meeting have sold three complex products in one single contract We need sellers who understand the deal behind the deal, design the path to get there, pull in the right people, and close. The role: full cycle, selling across the entire Blockworks platform. You'll work directly with our Co-Founder and our Head of Commercial. You need to know how to sell into founders and executives. Travel is part of the job. We host conferences in London, Singapore, and New York. We have an office in New York, but big deals don’t close sitting behind a desk. Blockworks is scaling very fast. Our systems are imperfect, our products ship fast, and our map gets redrawn all the time. If you need clean lanes, this will fr

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Member of Technical Staff, Search Why this role? We are looking for talented individuals to help us develop state-of-the-art models for information retrieval as part of our Search team. This group is working on a range of tasks including training our embedding and reranker models. You'll have the opportunity to revolutionise people's search experience by contributing to building an intelligent, efficient and precise search system and you would have a lot of opportunity to try new things out, innovate, and productionize your ideas. Your work will specifically focus on advancing semantic search techniques to improve accuracy and efficiency, involving working with a wide range of novel technologies and collaborating with other teams to integrate your work into our search infrastructure. We're looking for someone who is passionate about search and has a strong background in information retrieval. Candidates should have experience working with a wide range of technologies and have worked collaboratively with other teams in the past. As a Member of Technical Staff on this team, you will: Design, train and improve upon cutting-edge sea

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by leading the design of high-performance, scalable and reliable machine learning systems? Do you want to set technical direction and help shape the next generation of AI platforms powering advanced NLP applications? We are looking for a Lead Member of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will provide technical leadership across multiple teams, driving the architecture and strategy for deploying optimized NLP models to production in low latency, high throughput, and high availability environments. You will serve as a key point of contact for customers, leading the design of customized deployments to meet their specific needs, and mentoring engineers to raise the technical bar across the team. You may be a good fit if you have: 8+ years of engineering experience running production infrastructure at a large scale, with a track record of technical leadership Demonstrated experience leading the architecture

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 Sentry already has a startup program: credits, partner deals with YC and a16z, a landing page with a terminal theme that developers actually think is cool. What we don't have is someone whose full-time job is making this program a real growth engine. That's this role. You'll own startup marketing end-to-end: the partner ecosystem, the community presence, the acquisition programs, the brand in rooms full of founders and early engineers. You'll take what exists today and turn it into something that makes Sentry the default monitoring choice for every new company shipping code. This role reports to the Head of Enterprise Marketing (yes, we get how this can be confusing, but she’s pretty cool) and works across Growth, Product Marketing, and DevEx. You'll have real autonomy to shape the strategy and build programs from scratch – but you'll also need to execute quickly, (kind of – we can explain more) measure what works, and kill what doesn't. In this role you will Build and scale startup partnerships. Expand relationships with accelerators, incubators, VC platforms, and startup deal aggregators. Make Sentry's credits program a no-brainer inclusion in every startup perks stack. Own the startup acquisition funnel. Design programs that move early-stage companies from free plan → credits program → paid customers → expansion. Instrument everything so we know where the pipeline is and where it leaks. Be Sentry's face in the startup ecosystem. Show up at demo days, founder events, and SF tech week. Build relationships with the people building the next generation of companies. Not because it's a line item, but because you'

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity: Datadog’s Staff Engineers are our technical leaders operating at the forefront of technology, building solutions that take us through at least our next five years of growth. They do this in three major ways: As individual contributors, they bring world class technical abilities to deliver industry leading systems in areas such as data visualization, virtual runtime profiling, and planet scale streaming. As technical leaders they bring experienced technical breadth and communication skills to tackling design and architectural problems spanning the organization, charting the right course, then leading delivery. In both roles they participate in the staff engineering community and help us learn from what the industry is doing and what we've built before, and so improve company wide standards around software and systems engineering. Some examples of projects a staff engineer may own include designing and building a new data storage engine handling hundreds of millions of records per second, being the lead engineer building a new product like synthetics or profiling, or rebuilding a critical service to handle the next two orders of magnitude of scale. What You'll Do: Be the technical owner of multiple pieces of critical architecture in your area of the business Own delivery of the systems you architect from beginning-to-end, doing what it takes to get things shipped and at full scale in production Dive deep into performance of systems; inventing new approaches that bring efficiency at scale Who You Are: You have a BS/MS/P

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture, datasets and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. Recent examples of artifacts with major contributions from our team include GPT4-Turbo, GPT-4o and o1-mini. About the Role As a member of the architecture team, you will push the frontier of architecture development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in San Francisco. 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, prototype and scale up new architectures to improve model intelligence Execute and analyze experiments autonomously and collaboratively Study, debug, and optimize both model performance and computational performance Contribute to training and inference infrastructure You might thrive in this role if you: Have experience landing contributions to major LLM training runs Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion Are motivated by safely deploying LLMs in the real world Are well-versed in the state of the art tran