Staff Platform Engineer in United States

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

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. 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 help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

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,

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

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

Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection. We have a presence across the US and Europe including New York, Dublin, Seattle, Palo Alto, and Chicago. We support office-based and remote work and align projects with convenient work hours for each time zone. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database. ​​This role can be based out of our US offices or remotely in the North America region. Candidate Profile 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems Position Expectations Innovate in the area of flexible schema d

Join the MongoDB Server Query Execution team, and help us build a world-class distributed open-source database. Our team plays a crucial role in the performance and efficiency of MongoDB's data processing. We are responsible for building and improving the core execution engine that powers all queries, taking a logical query plan produced by the optimizer and turning it into reality. This includes developing the physical operators for data retrieval and manipulation, improving the runtime for complex analytical and transactional workloads, and owning critical components such as our new execution engine. In addition to the core server, we support the query execution needs of other major products like Atlas Streams, Atlas Search and Vector Search, and mongosync, making our work vital to the entire MongoDB ecosystem. You will be joining a globally distributed team with a significant presence in both North America and Europe. While this role is based in the NAMER region, you will regularly collaborate closely with colleagues across different time zones. We support both office-based work in our North America hubs like New York, as well as remote work. We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. To meet the ever-increasing data demands of modern applications, we are actively evolving our query system; this includes strategically re-architecting and improving key components of our query execution engine. We need your help to design and build the core of a distributed, flexible schema document database. This role can be based out of one of our North America offices, such as NYC or Palo Alto, or remotely across North America. Candidate Profile 10+ years of hands-on, professional experience in query engine development or database internals Experience with building production-level code with a large user base, robust design structure and rigorous code quality Degree in Computer Science or

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. NOTE: This role is hybrid and will require the candidate to be based in San Francisco Bay area. The successful candidate will be expected to work from the San Francisco office at least 2-3 days per week. The Community You Will Join: Research has been part of Airbnb from the beginning, ever since Paul Graham told the Airbnb founders, "go to your users." As designers, the founders embraced this advice and got on a plane to meet with Airbnb hosts that very weekend. Since those early days, the value of research has been baked into Airbnb’s product culture. With over 5 million hosts and 2 billion global arrivals, payments are crucial to the experience. Every time a guest books or a host gets paid across 190 countries, they rely on a seamless system. When it works, it drives loyalty; when it fails, it costs bookings—making research in this space critical to our business and our mission of belonging. The Difference You Will Make: As a Staff UX Researcher on Payments, you will be the voice of this community. In this mixed-methods role, you will combine behavioral insights with quantitative data to navigate ambiguity and global complexity. By uncovering user-centered insights and leading cross-functional workshops, you will drive actionable product innovation and build confidence into every transaction—from a first-time guest in São Paulo to a Superhost in Seoul. A Typical Day: Own end-to-end guest payments research, effectively prioritize research across multiple workstreams, plan and execute both foundational and evaluative research that shapes strategy and sharpens payments product experiences. Bala

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. NOTE: This position is US - Remote Eligible, but includes monthly in-person working sessions at the San Francisco Airbnb office. The Community You Will Join: Research has been part of Airbnb from the beginning, ever since Paul Graham told the Airbnb founders, "go to your users." As designers, the founders embraced this advice and got on a plane to meet with Airbnb hosts that very weekend. Since those early days, the value of research has been baked into Airbnb’s product culture. The Difference You Will Make: We're building our newest incubation work stream, and we're looking for a Staff UX Researcher who is equally strong in qualitative and quantitative methods. You'll be one of the first researchers on the ground for a 0-to-1 effort, which means the questions aren't defined yet, the roadmap will change, and your research will shape both. You'll know when to run fast to unblock a decision and when to go deep to get it right, while bringing senior stakeholders along the way. A Typical Day: Own end-to-end research for new incubation areas, from framing the questions to landing the recommendations. Utilize appropriate qualitative and quantitative methods to deliver fast, actionable insights. Triangulate across data sources and past learnings to get to the right signals in an ambiguous, fast-moving space. Balance speed and rigor: deliver quick reads when the team needs to move, and deeper studies when a decision warrants it, without sacrificing quality. Partner closely with cross-functional teams including Product, Design, Business Operations, and Data Science to shape strategy from research insights. C

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb’s mission is to create a world where people can Belong Anywhere. As we work to achieve that mission, we’re building world-class learning experiences for our technical teams. We’re looking for an exceptional and creative individual inspired to deliver innovative learning experiences that have tremendous organizational impact. The Difference You Will Make: The Staff Program Manager, Technical Education will play a key role in executing various technical learning programs including our Engineering Education programs that currently focus on AI Education, and other engineering and data education programming. Our focus is on impact and experimentation, creating world-class programs that enable technical excellence. We’re employing best practices from learning science and using measurement to iterate on learning experiences. The ideal candidate is confident in their ability to develop scalable learning experiences that drive overall growth and development for our technical audience. We are looking for someone who has the ability to synthesize a range of concepts into unified experiences, stay up to date in a rapidly shifting technical ecosystem, establish systems and processes, and deliver top notch program management. A Typical Day: Collaborate on and develop program strategy for various technical programs, including AI Enablement, AI Education, Machine Learning Education, Data Education, Engineering Education with internal SMEs and other Technical Learning & Development team members Design, create content, and project manage in-person and virtual technical learning

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join The Guest Engagement AA sits within Marketing Analytics and serves as the analytical backbone for Airbnb's lifecycle marketing programs — the email, push, and in-app communications that reach hundreds of millions of guests across their entire journey. You'll partner closely with Guest Engagement Marketing, MarTech Data Science, and Strategic Finance to drive measurable booking impact through experimentation and insights. The Difference You Will Make You will be the clear analytics owner of Airbnb's guest lifecycle marketing domain — covering abandon journeys, demand generation, onboarding, upsell, and more. This role is expected to drive significant incremental bookings in 2026 by setting the analytics strategy, designing rigorous experiments, and surfacing proactive insights across 30+ active programs. A Typical Day Own the analytics roadmap for Guest Engagement — define what to measure, what to test, and where the biggest opportunities lie across the full guest lifecycle. Specific projects and prioritization decisions should exist because of your recommendations. Design and analyze experiments at scale across abandon journeys, demand gen ML model rollouts, and placement-level A/B tests. Develop measurement frameworks (holdouts, proxy metrics, annualized impact models) to accurately attribute cumulative program impact. Surface proactive insights that go beyond reporting — user segmentation, funnel analysis, fatigue signals, channel optimization — and translate them into strategic recommendations for Director-level marketing leaders. Build scalable, self-serve reporting (