Staff Forward Deployed Engineer Jobs

We’re looking for a Staff Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you’ll set technical direction and build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents. This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. Set technical direction for the team, balancing experimentation with reliability, maintainability, and long-term platform thinking. Partner cross-functionally with teams across the engineering organization to understand engineering needs, identify workflow friction, and scale high-impact solutions

Every large organization has the same problem: too many projects, not enough visibility into who's actually available to do the work. Operations teams, PMOs, and professional services firms are making staffing decisions in spreadsheets, guessing at utilization, and finding out they're over-capacity after it's too late. Resource Management (RM) is Asana's answer to that problem — and we're at an inflection point in how we think about it. RM has strong foundations and proven enterprise demand, but it was built for a pre-agentic world. The next version of this product looks fundamentally different: AI Teammates that monitor utilization in real time, flag staffing risk before it hits delivery, recommend rebalancing across teams and projects, and automate the operational overhead that makes resource planning so painful today. We believe this capability is worth investing in seriously — not just as a feature within Asana's broader platform, but potentially as a standalone commercial offering for enterprise buyers whose primary need is resource visibility, not work management. As a Staff Product Manager leading this reinvention, you'll own the full RM product strategy — global capacity planning, skills-based staffing, time tracking, utilization reporting, and the agentic workflows that make all of it proactive rather than reactive. The strategic questions are genuinely open: what does RM look like as a reimagined agentic product, who is the right buyer, and how do we price and position it as a commercial offering in its own right? This role shapes those answers. This role is based in our New York office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. W

The AI Retrieval team powers the intelligence behind Asana's AI features by finding relevant work graph content and delivering it to LLM context windows. Our work enables AI features that truly understand your work—both within and outside of Asana—and use that understanding to take action. We also own Asana's traditional search experience. As a Staff Software Engineer on the AI Retrieval team, you'll build the systems that make Asana's AI smart and responsive. You'll tackle challenging problems in search and retrieval, working to improve the speed, cost-efficiency, and quality of our systems while expanding their capabilities to new data sources. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you'll achieve Reduce the latency and cost of our retrieval system, making Asana's AI features faster and more efficient Improve the quality and relevance of search results to help users find exactly what they need Expand the retrieval system's capabilities to query new Asana objects and third-party data sources Build and optimize search infrastructure using OpenSearch/ElasticSearch Contribute to ML-powered features like embeddings-based retrieval and semantic search Collaborate with cross-functional partners in New York City while building strong relationships with your Warsaw-based peers About you 6+ years of experience writing code in a production environment Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making Hands-on experience in search engineering, including with OpenSearch or ElasticSearch E

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

As a Staff Engineer on the Data Platform Experience team, you'll help shape how Datadog engineering teams build, operate, and evolve products on the Observability Data Platform. You'll lead the design and delivery of shared platform capabilities that reduce developer friction, improve operational visibility, and enable engineering teams to move faster with confidence. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in the code. You'll have the opportunity to solve company-wide challenges spanning cost intelligence, operational tooling, platform health, and developer experience. 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: Lead strategic engineering initiatives that improve how product teams build, operate, and evolve services on the Observability Data Platform. Design and build scalable platform capabilities for cost intelligence, including cloud cost allocation, trend analysis, and optimization recommendations. Develop operational intelligence and self-service tooling that helps engineering teams understand platform health, troubleshoot incidents, and improve operational efficiency. Drive reusable platform services and developer workflows that increase engineering autonomy while reducing operational complexity across multiple products. Provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on technical contributions. Participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence. Who You Are: You have experience designing and building large-scale SaaS or cloud platforms with deep expertise i

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,

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

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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: Lead the architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

Our Staff Developer Advocates are technical leaders and mentors that anchor our team. They own projects from beginning to end, facilitating collaboration and enabling Datadog's community to solve real-world problems. Based in Singapore and supporting the broader Asia Pacific and Japan (APJ) region, this role will enable our community of engineers around Datadog to be part of a movement of building better software. You will work closely with internal product and engineering teams, as well as Datadog’s customers, coaching and enabling them to deliver compelling talks and stories to practitioners. This is a unique opportunity to leverage both your engineering expertise and creative storytelling skills to shape the ever-evolving technological landscape. 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: Act as a subject matter expert for the Datadog advocacy and engineering teams Drive approach and execution of our overall first party technical event content programs in the region, such as Datadog Summits and engineering meetups, to tell authentic, compelling educational and inspirational stories for technical audiences Define and drive our regional advocacy programs for technical audiences, ensuring Datadog remains relevant to technical practitioners Represent Datadog’s point-of-view in the field to technical audiences at events and conferences. Manage, mentor, and grow a team of regional Developer Advocates based across APJ to execute localized community and advocacy strategies. Partner with and coach internal product managers and engineers on effective public communication and presentations for the work they do Represent Datadog point-of-view for our solutions, engineering culture and industry trends that our tec