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We are looking for a strong technical leader to join the Private Action Runner team, part of the larger Action Platform group and help shape one of the core execution layers behind Datadog’s action-taking and remediation capabilities. Private Action Runner (PAR) enables Datadog products and AI agents to securely run actions inside customer infrastructure with controls for authentication, permissions, auditing and safe execution. The role will be hands-on, covering architecture, implementation, reliability and collaboration with teams integrating PAR across Datadog. It also offers leadership exposure through leading a team of 3 engineers, with the expectation that the role will quickly transition into a formal Engineering Manager 1 position as the team grows. 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: (Describe role responsibilities here) Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Mentor and lead a small team of 3 engineers Who You Are: (Describe role qualifications here) You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI

The product operations team enables product excellence at scale at Datadog. With over thirty standalone products on a single platform, product operations drives consistency, efficiency, and quality across the organization. As a Product Operations Manager, you will help the product organization do its best work. You'll build and scale the processes, frameworks, and cross-functional workflows that enable PMs and their partners to ship effectively. This includes touchpoints with inbound, delivery, outbound workstreams in product development. This is a role for someone who thrives in the space between teams: driving alignment, removing friction, and ensuring that the operational foundations of the product org can keep pace with Datadog's growth. 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 and improve the full Product Development Life Cycle . Own and drive operational excellence for product launches. This includes coordinating across Product, Engineering, Marketing, Sales, Customer Success, and Support to ensure we are ready to bring quality products and support to our customers. Build AI-powered workflows and agents that automate and accelerate operational work. From customer feedback triage to launch tracking to cross-functional reporting, you'll experiment with and deploy AI tools and custom agents to help the product org move faster and smarter. Build and maintain a single source of truth for launches giving cross-functional partners real-time visibility into what's shipping, when, and what's needed from each team. Drive centralized product knowledge and enablement , ensuring PMs and stakeholders have the tools, resources, templates, and context they need to succeed and making it easily discoverable. Analyze and quantify product signals. Query pro

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI 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: Own the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

As organizations rapidly adopt AI applications and agentic systems, security teams need visibility and control over how these technologies are being used. Datadog's AI & Data Security product helps customers discover, secure, and govern AI usage across their environments ensuring sensitive data is properly managed from model training through production. As a Product Manager II for AI & Data Security, you will own capabilities for AI discovery, posture management, and data security; giving customers complete visibility into their AI applications, agents, and enabling ecosystem, with prioritized actions to operate AI systems securely. You'll partner with engineering, design, security research, and GTM teams to define and ship platform capabilities that help organizations adopt AI 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: Own the roadmap for AI & Data Security capabilities, including AI and data discovery & posture management. Define how security teams can assess and manage the security posture of AI-enabled systems, including configuration risks, sensitive data exposure, and policy violations. Work closely with engineers and designers to deliver new product capabilities end-to-end, from early concept through launch and iteration. Partner with Datadog security researchers to identify emerging risks in AI systems and translate them into actionable product features. Engage with customers to understand how they are adopting AI and validate solutions that help them operate these systems securely. Collaborate with go-to-market teams to enable adoption and communicate the value of AI security capabilities to customers. Who You Are: You have 3+ years of product management experience building technical products, ideally in security,

Datadog is looking for a Senior Product Manager to help lead the evolution of our fleet and lifecycle management capability, the product surface that gives customers visibility into, and control over, the observability software running across their infrastructure. This capability manages the deployment lifecycle for core observability agents and OpenTelemetry collectors running on customer hosts and containers. The Senior PM will expand the scope of fleet capability to additional Datadog software components, making it the single place customers go to see everything running in their environment, at any version, in any deployment model, and to manage it remotely and safely at scale, for both human operators and, increasingly, AI agents acting on their behalf. This is a high-visibility, cross-functional role. You'll partner with multiple engineering teams and be responsible for defining and delivering a coherent, unified fleet experience across UI, API, and MCP for customers. 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 and evolve the product vision and roadmap for a unified fleet and lifecycle management capability spanning multiple product lines and deployment models. Define what "managed" means for each new software component as it's brought into fleet, balancing consistency of experience with the realities of each component's operational model. Drive a phased expansion plan, sequencing new components into fleet based on customer value, technical complexity, and dependency readiness. Partner closely with engineering leads across several teams to align on shared architecture principles to support disparate software components. Represent the voice of the customer for a capability that must work equally well for human operators using a UI and for AI

As a Senior Platform Product Manager focused on AI SDLC Trusted Throughput, you will define and drive the product strategy for enabling safe, reliable software delivery at AI-native scale across Datadog’s Internal Developer Platform. As AI accelerates development velocity and system complexity, you will help evolve SDLC systems from human-supervised workflows to platforms with built-in safety, observability, and correctness guarantees. You will partner closely with engineering, security, and developer platform teams to improve deployment reliability, operational visibility, and governance while enabling both engineers and AI agents to move quickly with confidence. This role offers the opportunity to shape foundational developer infrastructure and influence how AI-powered software delivery operates across Datadog. 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 product strategy, roadmap, and execution for AI-native SDLC throughput and reliability initiatives across Datadog’s Internal Developer Platform Define and drive platform outcomes aligned to DORA metrics, balancing deployment velocity with reliability, change failure reduction, and operational safety Partner with engineering, infrastructure, security, and developer experience teams to build automated validation, auditability, and risk-scoring capabilities into deployment workflows Deliver actionable SDLC observability and diagnostic capabilities that connect executive-level metrics to operational signals across the software delivery lifecycle Drive systems that monitor and validate AI-generated or AI-attributed changes to ensure correctness, compliance, and trustworthy automation Serve as a cross-functional product leader across SDLC Foundations, Security Engineering, and compl

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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 strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

We are seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. Tens of thousands of customers depend on our Observability stack to monitor their database clusters and to generate actionable alerts to safeguard critical workloads. The Collections team is a newly formed team within MongoDB's Observability & Adoption Org focused on making telemetry onboarding and collection significantly easier across MongoDB. We own key parts of the observability collection stack, including onboarding experience, telemetry collection agents across the data and control planes, and ingestion services for metrics, logs, and traces that support both internal and customer observability in MongoDB, driving insights, recommendations, and alerting. Our mission is to reduce friction for teams implementing and iterating on Observability while partnering closely with development teams to instrument their services using shared best practices, helping define the conventions our telemetry should follow, and building collection and ingestion systems that are stable, performant, secure, well-documented, and self-service. We also work closely with the Data Pipeline and Storage & Query teams to help ensure MongoDB has a stable and performant observability stack end to end. This is an opportunity to join a team shaping how observability works across MongoDB and to have outsized impact on both the developer experience and the reliability of the platform underneath it. As MongoDB Atlas and its supporting infrastructure continue to experience rapid growth, the demand for high-cardinality observability data for internal and external use cases means we need to continually innovate and scale our systems to the next level. For example, MongoDB Observability systems need to handle 10’s of billions of metrics time series, all whilst processing petabytes of logs, traces, and events. Our stack includes VictoriaMetrics, Grafana, Sp

Our Internal Data team is on a mission to power decisions and applications across MongoDB, oriented around the business areas of GTM, Product & Technology, Finance and HR. With this role, we are focusing on delivery of scalable, insightful, and impactful data products for our Product and Technology (P&T) teams - the org that builds MongoDB products for our external customers. These products drive smarter decisions, automate workflows, enable AI agents and deliver actionable insights that accelerate growth. If shaping the future of data-as-a-product excites you, then this opportunity is for you. As a Senior Data Product Manager on our Data team — which includes Data Pipeline/Platform Engineering, Data Architecture, and Data Governance — you will lead efforts to build, enhance, and scale the data products MongoDB employees use every day across a growing, high-impact company. You’ll deliver data products like data pipelines, datasets, reports/dashboards, APIs, ML models, playbooks, and frameworks while enhancing more traditional data management tools/services to power both AI and BI. These data products form the backbone of our internal data ecosystem and are instrumental in empowering teams to achieve their KPIs and innovate faster. In this role you will also have the opportunity to drive the vision and strategy for internal data as a product, with a focus on telemetry and product adoption/engagement/churn signals. By developing tools and systems that provide deep insights into how customers use or don’t use MongoDB’s products, you will empower teams to understand customer behaviors and improve the end-user experience. The goal is to enable data-driven decisions that enhance product design, drive customer value, and fuel innovation across the MongoDB portfolio. This role can be based out of our Palo Alto, San Francisco, or New York City office or remotely in the East Coast region. Responsibilities Lead Product Strategy and Ownership Define product vision, stra

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. At Okta, we’re building the future of secure, enterprise-grade AI Agents . We’re looking for a Principal Engineer to join our global AI Engineering team. In this role, you will be instrumental in designing and building the intelligent, user-facing experiences and the end-to-end AI solutions that power them. This is a senior individual contributor role for a hands-on engineer who can set technical direction, mentor others, and partner closely with our cross-geo counterparts as part of one global team. What you'll do : Drive the architecture and design of AI solutions, leading cross-functional initiatives across Product, Design, and Data Science. Design, build, and refine the core backend services that power our AI solutions, including LLM orchestration, RAG pipelines, and generative AI features. Build high-performance Agentic Experiences (AX) for web and mobile, engineered for streaming responses and low latency. Champion observability and operational excellence to ensure our AI services meet enterprise-grade standards for reliability and performance. Develop robust backend services to power our AI solutions, including LLM orchestration, RAG pipelines, and generative AI features Enable the successful delivery of key AI projects through technical leadership and hands-on execution. Mentor engineers, raising the bar on technical craftsmanship and solution quality across the full stack. Collaborate with cross-geo peers to ensure globally aligned designs, shared

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! At Figma we believe design doesn’t end in a file or with your designer - it includes everything that goes into the product you ship: the production code that ties it all together, the systems and developer tools that make that code reliable, the context you provide to our AI agents, and the documentation that keeps everyone on the same page. The Code Area at Figma is redefining how Designers, PMs and Engineers collaborate. We are responsible for agentic workflows enabling ideation and prototyping on production codebases as well as accelerating the journey from design to code. In 2023, we launched Dev Mode , a suite of features that give developers everything they need to navigate design files and transform designs into code. In 2025, we introduced Figma’s MCP , accelerating how ideas get to production. Looking to the future, we aim to further reduce the barriers between design to code and code to design allowing ideation, prototyping and productionisation to happen seamlessly where it most makes sense. Our Code organization is expanding, and we’re hiring AI Product Engineers across multiple levels in the UK. We’re looking for people who have built generative AI products and are eager to lead AI efforts end-to-end, from early ideas to production. Join us in shaping the future of AI at Figma! What you’ll do at Figma: Build and evolve Dev Mode our MCP tools and Make -, Figma’s leading tools for dev/design collaboration Take part in building new 0→1 products within the agentic coding space Collabora

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. The Global Support & Partnerships team is a critical and unique part of helping Lyft succeed in our purpose to Serve and Connect. We support Lyft's international growth by developing integration platforms that seamlessly link global customers to an exceptional customer care experience. We go beyond simply supporting customers; we build the foundational infrastructure that turns every support interaction into a moment of genuine connection. Whether supporting our established North American community or welcoming new users worldwide, we ensure a unified, reliable, and efficient experience for riders, drivers, applicants and support agents alike. We are looking for an experienced technical leader who can support our global ambition by designing, owning, and scaling the Global Support Platform. Responsibilities: Set the technical vision and strategy for a rapidly evolving product area, making high-judgment calls on architecture and technology direction Drive the adoption of AI and machine learning solutions to optimize customer support workflows and enhance operational efficiency across the platform. Lead a team of talented engineers who ship code and tackle hard engineering problems, maintaining a high bar for technical excellence Translate high-level business goals into actionable engineering projects. Own the technical roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Drive the responsible adoption of AI development tools across engineering teams - modeling effective use, establishing best practices, and mentoring engineers to improve productivity without compromising code quality or security. Champion improvements in system, observability, performance, and tech debt reduction, extending your influence beyond your immediate team. Establish best practices f

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. Important to read before submit application: This role must be physically based in China. The Community You Will Join: Community Support Engineering (CSE) has increasingly become a key driver of enabling Airbnb's core business. Community Support Engineering is responsible for the world-class technology, architecture, and solutions that power CS at Airbnb. The products and capabilities we build empower our guests and hosts, CS agents, and operations teams around the world. As a member of CSE in China, you will have a great opportunity to make lasting impacts on the Airbnb CS user experience. The Difference You Will Make: We are seeking a highly skilled and motivated engineer who is passionate about making a difference through their work. As a Staff Software Engineer, you will be the technical lead in a team of talented and diverse software engineers leading the project execution to improve Airbnb customers and agents experience. You will lead the team and work with global technical leaders to build and evolute CS engineering foundations, such as Routing, Data platform, Case management, foundational toolings etc A Typical Day: Collaborating with cross-functional partners to deeply understand business problems before developing project solutions. Leading the execution of projects across the full software development lifecycle, including technical design, implementation, testing, and deployment, ensuring solutions are high-quality, scalable, and performant; Driving productive and constructive technical discussions with peers and cross-team technical leaders in the global collaborati