Staff Visual Product Designer in New York

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

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 Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget

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. Security Engineering is the engineering function inside the Plaid security org that focuses on developing the industry-leading security systems and infrastructure. Security Engineering owns most of Plaid’s security-related infrastructure: secure data storage, key management systems, internal identity platform, internal authentication systems, internal permission management, and internal authorization service. We develop solutions across data encryption, key management, access control, and data loss prevention to protect sensitive consumer data. We believe in the Zero Trust security model and are always looking for ways to improve our authentication and access control platforms. About the role: You will develop security capabilities to secure Plaid infrastructure and sensitive data access. You will lead the team’s strategic planning in collaboration with the manager and other senior engineers. You will own, maintain, and build Plaid’s security infrastructure and services like IAM Gateway, Key Management System and Network Firewall. You will consult with product engineers to ensure Plaid services meet security standards. You will help educate and support other engineering teams to improve security in

We are looking for a talented engineer to lead evaluation of startup acquisition opportunities in the AI, cloud and security space. You will drive product evaluations, prepare and manage technical architecture discussions with target groups in Product and Engineering and provide roadmap suggestions for M&A and investments for Datadog. You will be a key partner to Datadog’s C-level leadership and highly visible at the most senior levels of Datadog. The role is reporting into the Senior Director of Product Strategy and falls within the Product organization. We are looking for an innovative and strategic thinker who is passionate about the latest tech being developed by startups in the cloud, AI and security space. The ideal candidate enjoys researching and evaluating new technologies, works effectively with cross-functional teams, and communicates opinions concisely to our leadership team. Broad understanding of relevant Cloud Technologies and deep understanding of the full coverage of Datadogs current offerings is necessary. The Corporate Development team is small and values authentic, strong-willed individuals who think creatively and proactively. This role leads technical due diligence from a product and architecture perspective across our acquisition pipeline. You'll scope and stand up proof-of-concept and sandbox environments to stress-test candidate products, then give an honest, unvarnished view of their quality and depth - the kind of assessment that holds up regardless of deal momentum. You'll assess technical architecture, flag the risks and open questions that matter most early, and turn that into a clear post-acquisition integration path. Working closely with engineering, you'll keep the evaluation focused on what's actually decision-relevant, then translate the findings into strategic recommendations for leadership and help carry the integration through by partnering with the right people on the other side. What You’l

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

We’re looking for a Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. 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: Act as a technical leader within the APM organization, driving GenAI/machine learning projects from concept to production. Build and benchmark GenAI/ML models using state-of-the-art techniques. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, scaling challenges, and evolving requirements with clear technical direction. Actively mentor engineers and influence engineering culture through leadership in design reviews, technical talks, and working groups. Who You Are: You have a BS/MS/PhD in a scientific field or equiva

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. 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: Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

About the role: Datadog is building a product-led Competitive Intelligence function to help inform product strategy, roadmap prioritization, positioning, and competitive readiness. As the Head of Competitive Intelligence you will build and lead the CompIntel function across priority competitors and adjacent market opportunities. You will translate competitor product evolution, technical capabilities, launches, pricing value, customer sentiment, analyst narratives, and ecosystem shifts into actionable insights for Product, GTM, Sales Engineering, Customer Success, Technical Advocacy, and leadership. In this highly technical, hands-on leadership role, you should understand how observability products are implemented, where workflows differ, what technical claims are credible, and how product gaps translate into customer impact. What You'll Do: Own the recurring competitive radar for Datadog’s priority competitor set, including taxonomy, source standards, evidence quality, and update cadence. Produce competitive deep dives, feature-gap analyses, early-warning briefs, and opportunity assessments tied to specific product domains and leadership questions. Translate CompIntel findings into roadmap recommendations, product differentiation hypotheses, and Product-facing decision guidance. Build and maintain a central CompIntel repository with competitor profiles, source notes, comparison frameworks, evidence logs, and decision-ready briefs. Convert validated findings into GTM-ready handoffs for battlecards, objection handling, strategic deal narratives, and field enablement. Synthesize signals from Product, Engineering, Sales Engineering, Customer Success, field teams, technical communities, Advocacy programs, win/loss, customer feedback, analyst research, public competitor materials, and CABs. Partner with Product Management to frame competitive questions, identify decision criteria, and connect findings to roadmap and prioritization discussions. Partner with Tec

Role Summary: Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines with log management software that customers deploy and manage in their own infrastructure. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at scale. 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: Make customer-controlled deployments feel like a managed Datadog product: deployment, upgrades, configuration, observability, diagnostics, reliability, and secure operation across diverse customer cloud environments Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably that customers deploy and operate within their own cloud infrastructure. Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have significant experience building software that is installed, deployed, and operated in customer environments rather than only as a fully managed SaaS service. You have strong expertise in distributed systems,

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

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

As a Staff Product Manager on Datadog's Observability Data Platform (ODP) , you will lead product management for a portfolio of foundational platform bets — work that changes the cost structure and capability of the platform itself, not the cost of any single feature. Among ODP’s portfolio of engineering work are efforts to bring the platform's unit cost down meaningfully each quarter, plus a slate of architectural bets aimed at order-of-magnitude cost reduction over the longer horizon. The work you'll lead reshapes how Datadog ingests, routes, and exposes telemetry value to customers — and is foundational to how every product team in Datadog's ecosystem will think about telemetry economics going forward. This role reports to the Group Product Manager of ODP. What You'll Do: Set product direction across foundational platform bets by defining problems and desired outcomes, partnering with engineering to determine slices of work that drive value in phases for users and the business. Collaborate on the long-term cost-and-value architecture of the platform — how value-aware telemetry, innovative data engines, and customer-facing cost stories fit together over multiple quarters. Develop and defend sizing and impact estimates for large, diffuse programs — credibly produce the analysis that engineering leadership and pricing partners need to make resourcing and prioritization calls. Anticipate and communicate market trends in telemetry economics and agentic observability and how they shape platform investment. Develop deep understanding of cost-to-serve by partnering with engineering on the unit economics of the data platform and bring that cost-profile understanding into collaborative discussions with product verticals about customer-facing trade-offs. Surface the customer-positive angles in cost work that engineering-led optimization tickets don't currently make visible. Deliver concise written and verbal communication to executive, engineering, and customer audien

We're looking for a Staff Engineer to join the Logs organization at Datadog and help redefine how our customers ingest, query, and derive insights from logs data. In this role, you’ll work closely with Product Managers and customers to drive complex initiatives across ingestion pipelines, search infrastructure, and intelligent log management capabilities - all while pushing the boundaries of what’s possible with AI and distributed systems. You’ll have the opportunity to lead efforts that shape the future of log management. 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: Partner with Product Managers to define ambiguous product requirements and determine the most impactful solutions for customers Lead technical strategy and execution and design systems surrounding log query performance and ingestion at scale. Explore and prototype new capabilities and collaborate with peers on initiatives spanning AI-powered log management, security and business operations, advanced query capabilities, and external data sources query capabilities. Mentor engineers across levels and contribute to growing a high-performing, collaborative team culture Who You Are: You have deep experience architecting and scaling backend systems, with a strong focus on data-intensive or distributed infrastructure You excel in ambiguous environments, demonstrating a mix of drive, curiosity and pragmatic decision-making You’ve partnered effectively with Product Managers and customers to define product direction and ship impactful features You have expertise in debugging complex systems and optimizing performance across real-time data pipelines You have experience in using AI agents tools in your day-to-day engineering practices You lead by example and enjoy helping others grow through m

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. About Fern, a Postman Company Fern helps software companies build a world-class API experience. Our customers include industry leaders like Nvidia, Square, and Twilio, as well as fast-growing AI companies like ElevenLabs and OpenRouter. In the next year, the majority of API integrations will be implemented by AI agents. Agents don’t read marketing pages. They need strongly typed schemas, structured endpoints, deterministic contracts, and documentation that can be fed into a context window. Our team is small and talent-dense. We’re a team of builders from Google, Palantir, Amazon, and Uber, working together in New York City. About the Role As a Staff Software Engineer at Fern, you’ll build APIs, scale AI infrastructure, and design developer experiences that reach millions of people. Set technical direction: Drive system design decisions around data modeling, performance, correctness, and reliability. Identify scaling bottlenecks before they become problems. Build for durability and scale: Ensure our systems are performant, observable, secure, and resilient under real-world production load across infrastructur

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: The Experience team is at the center of one of the most exciting transitions in software development history — the shift from human-driven to agent-driven product experiences. We own Pinecone's API, clients, authentication, revenue, and observability systems, and right now that means redesigning all of it for a world where AI agents are first-class users alongside humans. This is a wide-scope role. You'll own things end-to-end — from backend architecture to API design to SDK and web surfaces. You’ll be working closely with product, design, and other engineering teams to identify user needs and build the right thing, at the right abstraction level, at the right time. Along the way, you will be building high-leverage platform capabilities that accelerate Pinecone’s product development and user growth systems. We're looking for an engineer who sees this moment for what it is: a rare opportunity to shape how developers and agents interact with a category-defining product. You're not waiting to see how the industry figures out MCP, agentic workflows, and AI-native interfaces — you're already experimenting, already forming opinions, already building. You know that speed and leverage matter more than labor, and you've internalized AI-assisted development not as a productivity trick but as a fundamentally different way of working. Responsibilities: Pioneer our agent experience. Shape how AI agents interact with Pinecone — designing interfaces, protocols (MCP), and tooling that make Pinecone the easiest and most capable platform f