Product Support Engineer in New York

We’re looking for a Staff Product Designer to join the APM (Application Performance Monitoring) team. This team is focused on helping engineers agentically troubleshoot and optimize their applications. You'll learn the domain and proactively spot areas for improvement, getting stakeholder buy-in as needed. You'll own your design work end-to-end while helping shape broader product direction. You'll also hold a high bar for quality across the team and help other designers build support for their decisions. 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: Become a design leader within APM by proactively identifying opportunities and shaping the design strategy across multiple product areas and workflows. Partner closely with PMs and Engineers to ship intuitive experiences, balancing user needs with platform scalability and engineering constraints. Conduct and synthesize qualitative and quantitative research to identify pain points, validate solutions, and guide roadmap decisions. Communicate design rationale clearly and persuasively across design, engineering, product, and executive stakeholders. Mentor and support other designers by providing feedback, sharing frameworks and workflows, and helping raise the overall design quality bar across the organization. Prototype in code to rapidly explore ideas and validate concepts. Contribute to production code using AI-assisted workflows to ensure execution matches design intent. Help the team adopt AI-enabled design workflows. Who You Are: You have 10+ years of experience in digital product design. Your portfolio demonstrates a strong track record of designing and shipping complex technical products. You use AI-assisted workflows to prototype and rapidly iterate. You have a track record of connecting

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

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 looking for Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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 looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

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 builds AI infrastructure products that developers love. That's how we grew so quickly and why word-of-mouth remains one of our most important channels today. From powering one of the largest vibe-coding platforms at Lovable to enabling teams like Ramp to build their own internal coding agents , Modal Sandboxes are used by developers to safely execute AI-generated code at scale. We're now hiring our first developer relations engineer focused on Modal Sandboxes. Whether it’s banger tweets , in-depth technical resources or long-form talks , we want to meet developers by any medium necessary and empower them to build and ship novel AI products. In this role, you will primarily be creating and distributing technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcas

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 looking for an Infrastructure Security Engineer to design and secure the core systems that power our platform. This role focuses on building security directly into our infrastructure—from container isolation and orchestration to identity and secrets management in a multi-tenant, cloud-native environment. You’ll work closely with engineering teams to define secure primitives and ensure our platform is resilient, scalable, and trustworthy by design. This is a hands-on, deeply technical role focused on real systems, not compliance or policy. What You'll Do: Platform & Runtime Security Design and improve isolation mechanisms for multi-tenant workloads (containers, sandboxing, execution environments) Strengthen boundaries between customers, workloads, and internal systems Identify and mitigate risks in distributed, dynamic compute environments Container &

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Backend Software Engineers at Palantir build software at scale to transform how organisations use data. Our Software Engineers are involved throughout the product lifecycle, from idea generation, design, prototyping, and production delivery. You will collaborate closely with technical and non-technical teammates to understand our customers' problems and build products that solve them. We encourage movement across teams to share context, skills, and experience, so you'll learn about many different technologies and aspects of each product. Engineers work autonomously and make decisions independently, within a community that will support and challenge you as you grow and develop, becoming a strong technical contributor and engineering leader. Your day-to-day workflow will vary, adapting to the requirements of our users and the technical challenges that arise. One day, you may find yourself collaborating with other engineers to architect a new system that enables a novel workflow, the next you could be fine-tuning performance to enable low-latency operational outcomes. Our Product Development organisation is made up of small teams of Software Engineers. Each team focuses on a specific aspect of a product and work collaboratively to build cross functional capabilities, streamline user workflows and continuously improve our software's efficiency and reliability. We’re hiring engineers who are passionate about solving real-world problems and empowering both developers and end-users to work optimally. If you’re motivated to develop reliable, performant, and scalable systems, and to design robust APIs and primitives, this role offers the opportunity to make a

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: 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

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. Today, CLEAR is well-known as a leader in digital and biometric identification, reducing friction for our members wherever an ID check is needed. We’re looking for a Senior Software Engineer to establish our Observability framework and foundations. You will join us to accelerate building and scaling our innovative systems that support our growing identity platform. You will drive on Observability best practices to find and fix gaps in our observability and our overall systems. You will also lead practices such as load testing, capacity planning, game days, chaos testing, and incident post-mortems. What You Will Do: Embed within the Engineering pillar to deeply understand the product and implement observability across all key flows Facilitate and build load testing cases, ensuring we understand the limits and scaling factors of our services and systems Contribute to observability and support the design of new services and systems, ensuring highly reliable and scalable concepts are implemented Build and lead practices such as game days, chaos engineering, and failure analysis Build long-term capacity plans, with an eye toward reliability and cost-efficiency Who You Are: 6+ experience writing production-grade software in a modern language, such as Java and Python. Strong knowledge of distributed systems concepts (think CAP theorem), microservices architecture, and distributed tracing . Experience with modern observability systems such as Datadog. Experience with performance debugging tools and patterns. You should be able to read a f

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Senior Software Engineer to join our Network Engineering team to accelerate building and scaling our innovative systems that support our growing identity platform. In this role, you will build the next-generation infrastructure that underpins all systems at CLEAR. The ideal candidate for this role will approach challenges with an eye toward reliability, simplicity, and scalability. What You'll Do: Develop and maintain a streamlined process for engineers to effortlessly build and deploy scalable and reliable software-defined networking solutions on AWS. Enhance our compute platform (Kubernetes) by integrating new functionalities and features, focusing on AWS networking services and concepts such as VPCs, Route Tables, Security Groups (SGs), ALBs/ELBs, and Route53, as well as implementing Kubernetes networking solutions like service mesh (Istio) to optimize service communication and management. Collaborate across engineering teams to advocate for and implement best practices in observability, utilizing tools like Splunk or Datadog to ensure robust network monitoring. Act as a product owner for our infrastructure, collecting feedback and requirements from engineering teams to address pain points and develop solutions, particularly in the realm of AWS networking and cloud-native design principles. What you're great at: 6+ years of extensive experience in infrastructure and platform development, particularly in software-defined networking and AWS cloud services. Proficient in writing production-grade softwar

As a Senior Product Manager for Regulated Industries, you'll drive our compliance, data sovereignty, and new market presence roadmap—one of Datadog's highest-growth focus areas. You'll work cross-functionally with teams across GTM , Support, Corporate Development, and fellow product managers to help accelerate that growth. A key focus of this role is international expansion across strategic markets, alongside supporting our ongoing regulated industries initiatives. At Datadog, we place real value in our office culture—the relationships, collaboration, and creativity it fosters. We operate as a hybrid workplace so our Datadogs can build a work-life balance that fits them. What You'll Do Define the roadmap for delivering Datadog's platform to highly regulated customers, globally Collaborate with product managers to help them succeed in regulated markets Speak fluently to the technical details customers care about—data flows and security architecture—for both engineering and executive audiences Enable GTM by partnering closely with sales and marketing teams Partner with Compliance Engineering and InfoSec teams Work with marketing, sales, and post-sales teams to identify gaps in our regulated offerings Deliver AI capabilities responsibly to highly regulated customers Who You Are You have five or more years of experience in a SaaS/B2B regulated industries role—Product Management, Compliance, Global Public Sector Engineering, or Product Marketing You're passionate about working with customers in regulated markets such as public sector, healthcare, and financial services You're customer-focused with high standards for quality You're energized by growth-stage opportunities You can engage deeply with technical, compliance, security, and executive audiences alike—from platform engineers to CISOs and CTOs You have excellent verbal and written communication skills, with the confidence to present ideas to technical stakeholders and executives alike You enjoy partnering cro

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