Staff Designer in New York

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. Our Credit team at Plaid is building the largest cash flow based Consumer Reporting Agency (CRA) in the US to deliver lending solutions across the full lender lifecycle — including underwriting, verification, and servicing. We help lenders make faster, more informed decisions using consumer-permissioned financial data. As the Product Manager for our CRA Network team, you will grow the number of consumers that have permissioned their data to our CRA, Plaid Check. You will build a more robust experience for consumers to interact with the CRA and learn more about sharing cash flow data with lenders. Responsibilities Own and accelerate the growth and health of our CRA network Drive credit initiatives across the broader Plaid network Own consumer consent UX experience including conversion and improvements Build trust through our CRA consumer experience Qualifications 5+ years of product management experience Must have built and owned a lending product at a FinTech Experience working on a growth product - especially on a network product Deep understanding of the E2E lending process from acquisition to originations to servicing Excellent communication skills and the ability to advocate f

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is uniquely positioned across the full consumer journey—from inspiration and discovery through consideration, planning, and action. Creators bring ideas to life, Pinners signal emerging interests and intent, and advertisers help people act on what inspires them. This role will define how Pinterest measures that flywheel, helping advertisers understand how Pinterest and its creators build awareness and drive business outcomes, while helping creators understand the value they generate and unlock new opportunities with brands. The ideal candidate is a Staff-level product leader with substantial ads measurement experience and a deep understanding of how advertisers set objectives, deploy tactics across the full funnel, and evaluate outcomes. They have worked cross-functionally with engineering, data science, research, PMM, sales, an

As a Forward Deployed Engineer on the Feature Flags team, you'll partner directly with customers to accelerate their feature flag implementations — from initial architecture consulting through prototype builds to full-scale migrations. This role is for someone who wants to write code with customers, not just advise them. You'll work hands-on inside customer codebases to unblock complex, high-stakes deployments, directly influencing deal velocity and customer success. Working closely with Sales, Solutions, and Engineering, you'll be the technical force that turns a signed contract into a live, adopted implementation. What You'll Do: Serve as the hands-on technical partner for strategic customers implementing Datadog Feature Flags, from pre-sales technical validation through post-sales delivery Consult on flag architecture and implementation approach for complex environments — multi-service, multi-platform, high-scale deployments Build prototype flag implementations directly in customer codebases to prove value and de-risk technical decisions early in the sales cycle Implement flags across diverse and advanced deployment modes (server-side, client-side, edge, mobile, streaming/real-time) tailored to each customer's stack Drive full flag migrations to completion — including legacy system cutover — efficiently and with minimal customer engineering burden Identify patterns across customer implementations and feed them back to Product and Engineering to improve the core product and reduce future implementation time Collaborate closely with Engineering on technical edge cases, product gaps, and implementation tooling Partner with Sales and Solutions to accelerate deal cycles by removing technical risk and uncertainty Who You Are: 5 years of professional software engineering experience, with hands-on coding ability across the stack you're deployed into Experience with feature flagging, experimentation, or config management systems (internal or vendor) Comfortable dropping i

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. We believe Plaid has the power to be the next-gen Credit Bureau - supporting large scale adoption of cash flow into the credit underwriting process. The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers. We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly. You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap. You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions. Responsibilities: Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training. Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors

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