Service Support in New York

Coordination Systems provides foundational distributed systems building blocks for internal Datadog platforms. Our services cover sharding, consensus, resource protection, configuration distribution, and much more. We are looking for a manager to lead the Coordination Systems - Storage team. This team provides essential configuration storage and distribution systems that are depended upon by almost every service and pod at Datadog. We power critical runtime configuration (e.g. feature flags), complex control planes (e.g. dynamic sharding configuration), and much more. Storage is one of four subteams within Coordination Systems. If successful, the candidate will have opportunities to lead other growing and impactful areas such as Resource Protection. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: (Describe role responsibilities here/max 6 bullets) Lead a core team of 5 engineers (distributed, with majority in NYC) Lead ceremonies, prioritize and delegate project Stay hands-on with the code, e.g. isolated features, small remediations, investigation follow ups Stay actively involved in operations, incidents, root cause analysis, etc. Constantly promote a culture of operational excellence, organizing gamedays, conducting operational reviews, staying proactive with reliability Who You Are: (Describe role qualifications here/max 6 bullets) Strong distributed systems skills, able to understand and account for a variety of failure modes, well-versed in end-to-end o11y, validation testing, simulation setup, etc. Worked on platform teams before, providing critical infrastructure to internal stakeholders Experienced in handling significant incidents, both as a responder and follow-up ow

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is building a centralized Pricing, Yield & Compensation function to bring rigor and visibility to how we price inventory, manage programmatic performance, and compensate our Ads and Lyft Business sellers. This is a high-visibility, cross-functional role sitting within the MBA StratOps function and touching Finance, Analytics, Sales, and Accounting daily. The Manager, Pricing, Yield & Sales Compensation will own three interconnected functions: setting and managing CPM floors, rate cards, and margin targets for our direct-sold advertising inventory; overseeing the performance and economics of our Audience Extension managed service; and partnering with Analytics and Accounting to design, calculate, and administer commissions and compensation for sellers across Lyft Ads and Lyft Business. This role requires an operator who is equally comfortable pulling margin reports, running a compensation calculation model, and holding a vendor accountable to a floor price. Responsibilities: Direct Inventory Pricing & Yield Management: Own the Lyft Ads rate card strategy across all direct-sold formats (display, in-app, sponsored placements) and enforce pricing discipline through the order management system, Boostr. Set and manage CPM floors and pricing tiers, and partner with Sales and Ad Ops to evaluate custom deal structures and non-standard pricing requests against margin thresholds. Monitor sellthrough, utilization, and margin by product line, and surface risks and opportunities in weekly and monthly yield reviews. Managed Service Performance Oversight: Serve as the internal owner of our vendor led Audience Extension managed service performance, holding the vendor accountable to agreed CPM targets, margin commitments, and delivery standards. Conduct regular performance reviews of Vendor campaigns,

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

Senior Software Engineer - Streaming Platform Client Data streams are mission-critical at Datadog, powering near real-time communication across the vast majority of our services. Our Streaming Platform group builds the core infrastructure and abstractions that ensure Datadog remains a trusted partner for engineers worldwide. See our blog post . The Streaming Platform Client team sits at the heart of this ecosystem. We own the Rust client library (producers and consumers) with language bindings for Java, Go, and Python. We focus on building intuitive APIs and abstractions that make a powerful distributed system easy to adopt and operate for the hundreds of internal users of our library. Our library runs on critical data paths that handle hundreds of millions of messages per second making performance, observability, and reliability paramount. We also develop and operate the service that bridges the clients fleet with the platform's control plane, handling complex balancing, scaling, and static stability challenges. We are seeking a Senior Software Engineer to help us evolve these features. You will collaborate directly with our users, tackle performance-critical code, and solve complex distributed systems challenges across the control plane, client libraries, and data plane. 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: Work within a distributed, high-impact team spanning Europe and the US, building critical technologies that power data pipelines for dozens of internal teams and hundreds of services. Architect and implement resilient interactions between our client libraries and the control plane. Optimize our high-throughput, low-level streaming library to push the boundaries of performance and efficiency. Champion the developer experience by providing

Senior Software Engineer - Streaming Platform Client Data streams are mission-critical at Datadog, powering near real-time communication across the vast majority of our services. Our Streaming Platform group builds the core infrastructure and abstractions that ensure Datadog remains a trusted partner for engineers worldwide. See our blog post . The Streaming Platform Client team sits at the heart of this ecosystem. We own the Rust client library (producers and consumers) with language bindings for Java, Go, and Python. We focus on building intuitive APIs and abstractions that make a powerful distributed system easy to adopt and operate for the hundreds of internal users of our library. Our library runs on critical data paths that handle hundreds of millions of messages per second making performance, observability, and reliability paramount. We also develop and operate the service that bridges the clients fleet with the platform's control plane, handling complex balancing, scaling, and static stability challenges. We are seeking a Senior Software Engineer to help us evolve these features. You will collaborate directly with our users, tackle performance-critical code, and solve complex distributed systems challenges across the control plane, client libraries, and data plane. 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: Work within a distributed, high-impact team spanning Europe and the US, building critical technologies that power data pipelines for dozens of internal teams and hundreds of services. Architect and implement resilient interactions between our client libraries and the control plane. Optimize our high-throughput, low-level streaming library to push the boundaries of performance and efficiency. Champion the developer experience by pro

As a Cloud Security Engineer you will partner with different stakeholders across the organization to secure our cloud infrastructure. As part of the Platform Security organization we secure the building blocks of Datadog’s applications and infrastructure. We do this by building solutions to solve systemic risks and combine an approach of making the secure path easier and the insecure path harder to secure and accelerate the business. We regularly partner with the most bleeding edge internal products and are working to solve and build solutions to enable our safe usage of AI. We also develop AI based solutions to enable security at scale. We are looking for a Service Mesh and Kubernetes focused security specialist to help round out an incredibly strong infrastructure security focused group. You will rotate through a variety of internal projects and gain deep exposure to Datadog’s infrastructure. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Solve our most challenging cloud infrastructure security problems starting with our core building blocks and golden paths. Enable our engineers to build and ship secure solutions quickly. Build and extend Datadog’s Platform Security solutions. Leverage and influence the direction of Datadog’s products to secure our infrastructure, and provide internal feedback that enables our teams to improve the products for ourselves and our customers. Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent professional experience. Passionate about advocating for and implementing solutions to complex problems, at-scale, in a large multi-cloud environment. You don’t want to just provide security recommendations, you want to help imple

About the team The Applied AI Engineer, Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our NYC office. 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: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships wi

Datadog's Software Engineers with Systems depth leverage their experience with systems and tooling to build software that ensures Datadog remains reliable, performant, and secure. For this track, their Software Engineering experience may resemble the Distributed Systems track, but is typically applied in combination with their systems experience to build and run internal platforms and tools that our products are built on. These people typically have deep experience building and managing large cloud infrastructure deployments, or leading reliability efforts for orgs similar to ours, or building release machinery to allow hundreds or thousands of devs to do their jobs without stepping on each others' toes. The systems and tooling where they may have experience depth may include (but not limited to): bazel, build tooling, cassandra, CDN, chef, configuration management, container orchestration, consul, docker, elasticsearch envoy, haproxy, kafka, kubernetes, load balancing, network architecture, postgres, redis, release management, RPC frameworks, service discovery, spinnaker, terraform, zookeeper. Bonus: You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #LI-KM5 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. Th

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

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. As a Senior Software Engineer, Data, you will design, build, and operate the next generation of our data platform and products – going beyond ID to power a networked digital identity – while keeping member privacy, security, and reliability at the core. What you’ll do: Build and operate scalable, reliable data systems and pipelines – from ingestion to modeling to visualization – so Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner. Develop and maintain end-to-end data products and pipelines (batch and/or streaming) that collect, clean, transform, and model data, and own the infrastructure that powers them to unlock new business use cases and reporting. Implement and maintain infrastructure-as-code, CI/CD, and shared developer tooling for data products (e.g., Pulumi/Terraform, GitHub, orchestration tools like Dagster/Airflow) to make it easy and safe for teams to build, test, and ship changes across environments. Improve the security, compliance, and cost posture of the data stack through robust dependency management, IAM and secrets hardening, observability, and performance/cost optimizations. Partner with product and other stakeholders to uncover requirements, make architectural decisions, and continuously improve our data platform and processes. How you’ll measure success: Data reliability & SLAs: % successful pipeline runs, adherence to freshness SLAs for core datasets, and reduction in data-related incidents impacting stakeholders. Platform quality & efficiency: Reductio

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 an experienced Software Engineer to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Software Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: Java / Kafka / Postgres AWS cloud What you'll do: Advance our capabilities across a wide array of industries and domains and gain hands-on experience with privacy, security, data modeling and architecture Develop and deliver code across the full stack, driving engineering excellence by defining to best practices in testing, documentation and observability Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you’re great at: 3+ years of backend software development experience in Java Working with cloud-based application development, and being fluent in at least a few of: Cloud service providers like AWS Containerization technologies like Docker and Kubernetes Collaboration, integration, and deployment tools like Github, Argo, and Jenkins Arti

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

As a Software Engineer - Frontend on a feature team, you'll be responsible for building an intuitive, responsive product. Your work will help thousands of customers to monitor the health and performance of their systems, no matter the scale. In this capacity, you’ll use tools like React and Typescript to help streamline the flow of data from platform to user, enable seamless pivots from one view to the next, and build a powerful yet easy-to-use platform. You will work on complex frontend challenges for thousands of customers with huge sets of data and work on exciting scalability and performance challenges. Our users are also developers so you will feel close to the product and have an impact on the development world. You will be part of a front-end community of 200+ passionate frontend engineers and you will be surrounded by experts. Join us to build the next generation of high-scale, data-powered features for our customers. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Work closely with backend engineers, product managers and designers to inform/refine/validate design concepts Break down complex features into distributable engineering tasks and rollout plans Design and deliver features that have direct impact on thousands of users Experiment with and advocate for new systems, design patterns, and tooling Participate in hackathons, sync with other Front end engineers at the monthly demos meeting and yearly Front End summit Use and contribute to a best-in-class in-house design system Own meaningful parts of our service, improve performance and address scalability limits Work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challen

Salary range - $250k - $350k | Equity - up to 0.5% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Research Engineer to own problems end to end across our models, inference service, and product. You won't just train a model and hand it off. You'll take it from training through benchmarking, into our inference stack, and work with the team to integrate it into our products. We're a small team that has shipped the current state of the art OCR model, Chandra. Our models collectively have 70k+ Github stars. Our tools are used internally at frontier AI labs like Anthropic, and Fortune 500 enterprises like Siemens. Our team focuses on training small, efficient models that outperform much larger LLMs on domain-specific tasks (like OCR, structured extraction, tables). We move fast, prioritize practical results, and build tools that are open, reproducible, and built to last. You'll test hypotheses quickly, iterate on results, and balance experimental rigor with shipping to customers. Day to day: A typical project might look like: identify a gap in extraction quality on long documents, train and benchmark a new model, optimize it for inference, and work with the team to ship it to users. Concretely: Train and evaluate models: Train task-