Lead Systems Integrator in United States

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

We are hiring a Senior Technical Product Marketing Manager to lead positioning and messaging and to grow adoption of MongoDB Search and Vector Search as foundational components of our platform – the retrieval layer powering the next generation of grounded AI applications and agents. This is a high-impact role for a marketer who thinks like a builder. As developers architect increasingly sophisticated systems – RAG pipelines, agentic workflows, multi-modal search experiences – retrieval has moved from an implementation detail to a core design decision. You’ll join a high-performing, globally distributed team and partner closely with Marketing, Builder Relations, Product Management, Engineering, Partners, and Sales to develop, measure, and achieve cross-functional goals. The role requires technical depth in information retrieval — lexical and vector search, hybrid approaches, embeddings, re-ranking, agentic retrieval loops, and the tradeoffs that matter in production systems — paired with the product marketing instincts to turn that depth into crisp, differentiated messaging for distinct user and buyer personas. Hands-on experience building or shipping AI-enabled products is a strong advantage. Individuals with prior experience in technical sales, developer relations, or technical marketing are encouraged to apply. This person is a voracious consumer of AI research and pays close attention to shifting patterns in application architectures and development, including agentic systems. This individual is confident in communicating with technical practitioners and non-technical decision makers in one-to-few and one-to-many engagements for internal and external audiences. We are looking to speak to candidates who are based in the US for our hybrid working model. What You’ll Do Drive Strategy & Execution: Act as a strategic partner for high-impact initiatives that align with MongoDB’s long-term business goals in collaboration with Marketing, Developer Relations, Product

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers with deep iOS or Android expertise and demonstrated experience contributing beyond mobile to frontend web or backend development. You’ll shape and build purchasing and subscription experiences across mobile applications, web, and supporting product APIs. The work spans improving conversion, performance, and reliability, building reusable components, and enabling new product launches. You’ll combine product judgment with technical depth to set direction, lead initiatives across teams, and remain hands-on through implementation and delivery. Approximately 50% of the work will initially be native mobile development, with the remainder across web and product APIs. We’re looking for engineers who enjoy working across the stack and have concrete examples of doing so professionally. Depth in either iOS or Android is required; experience in both is not required. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing and subscription experiences across native mobile, mobile web, and supporting product APIs. Partner with Product, Design, and Growth to identify customer needs, prioritize improvements, and shape technical direction for purchasing experiences. Improve conversion, performance, and reliability through experimentation, product analytics, and customer insights

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re hiring a Staff Machine Learning Engineer to help drive the future of merchant presence and shopping experiences on Pinterest. This role sits on the Merchant team and focuses on building AI/ML systems (including LLMs) that identify, understand, and surface relevant, high-quality merchants across segments—so Pinners can discover new brands with greater confidence and consideration, and merchants can reach new, diverse audiences. In this role, you’ll lead LLM-first, evaluation-driven initiatives—near-term focused on agentic workflows, measurement, and operational rigor that strengthen Merchant Integrity and Business Integrity. Longer term, you’ll help advance core relevance capabilities such as merchant/brand affinity modeling and related signals that improve shopping discovery across Pinterest. You’ll partner closely with Product Managers, E

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or c

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or co

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Team: Plaid is becoming an AI-first company, and Intelligent Tooling builds internal platforms and tools to lead the transformation. Our biggest opportunity isn't just better tools for engineers, it's extending AI-native internal tooling to the rest of Plaid. Tools built for engineers assume things non-engineers don't have: local toolchains, monorepos, engineer credentials, PR-based workflows. That mismatch means Ops, Support, and other teams can't easily inherit what we build for engineering. They need their own path and we're building that path. Role: As a Senior Software Engineer on Intelligent Tooling, you will build and operate internal systems that empower non engineering teams to automate their workflows with AI. You will own the product and platform layer for internal tools, including the constraints and infrastructure that keep those tools safe and maintainable. There's no existing playbook for this at Plaid. You will define what the right non-eng AI surface looks like, ship its first durable versions, and partner closely with internal users to make sure it solves real problems. You will act as the engineering point of contact embedded with non-engineering teams, running discovery and trans

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences – all created by our global community of developers and creators. At Roblox, we're building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We're on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you'll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Why Safety AI Systems? As Senior Engineering Manager for Safety AI Systems at Roblox, you'll lead technical efforts and manage a team of experienced engineers to develop innovative AI solutions for language and text content safety. You'll oversee machine learning systems, data quality, training pipelines, and model performance to address challenges like real-time content understanding across Roblox's experiences

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

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

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Conversion Visibility Modeling team enables a performant ads marketplace and helps prove value to advertisers by connecting Pinterest onsite activity with conversions that happen offsite (both digital and physical) in a privacy-preserving way. As a Machine Learning Engineering Manager on this team, you will lead a hybrid team of ML engineers and backend software engineers to build end-to-end identity and conversion visibility solutions across modeling, serving, and data infrastructure, so advertisers retain accurate, privacy-aware performance visibility as signals fragment and degrade. You will set the technical direction for high-impact ML systems that feed ranking, bidding, measurement, and reporting across Pinterest’s ads stack. What you’ll do: Attract, hire, develop, and lead a hybrid team of ML engineers and backend softwar

About the Role We're looking for a Head of Competitive Intelligence to build and lead a world-class competitive intelligence function. This person will transform market signals into strategic advantage by developing the frameworks, analysis, and insights that inform our product strategy, go-to-market approach, and executive decision-making. This is not a research role. It's a highly cross-functional strategy role that sits at the intersection of Product, GTM, Research, and Leadership. You'll establish the systems, operating cadence, and analytical rigor that help the company understand where we win, where we're vulnerable, and how the market is evolving. What You'll Do Build and own the company's competitive intelligence strategy and operating model. Develop and maintain comprehensive competitive assessments, including Harvey Ball analyses, feature matrices, product comparisons, pricing analyses, and market landscape reviews. Create executive-ready competitive insights that influence product strategy, roadmap prioritization, pricing, and investment decisions. Build best-in-class objection handling and competitive messaging for Sales, Marketing, Customer Success, and Partnerships. Monitor competitor product launches, model releases, acquisitions, partnerships, pricing changes, funding, and GTM motions, synthesizing complex information into clear strategic recommendations. Establish repeatable processes and tooling for collecting, validating, and distributing competitive intelligence across the company. Partner closely with Product Management to inform roadmap decisions and identify areas of strategic differentiation. Collaborate with Marketing to sharpen positioning and messaging based on competitive dynamics. Support executive leadership with board-ready competitive analyses and market briefings. Build dashboards and reporting that track competitive movements and emerging industry trends. Develop frameworks that evaluate competitors across capabilities, enterprise r

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,