Ai Engineering Director in New York

Datadog is seeking a highly motivated Senior Corporate Development Lead to drive our AI product strategy, build strong relationships across the founder and VC ecosystem, and support high-impact initiatives including acquisitions, venture investments, and startup partnerships. You will be part of a small, high-visibility team that reports directly to Datadog's Founder/CEO. The ideal candidate is passionate about AI and developer tools, comfortable rolling up their sleeves, and excited to operate in a fluid, technically demanding environment. You will support evaluations, source promising AI startups, collaborate closely with internal product and engineering leaders, and help position Datadog as the preferred partner for the next generation of founders. This role is ideal for someone who is hungry for increased responsibility, operates with authenticity and creativity, and prioritizes the company's interests. 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: Support Datadog's AI product strategy by analyzing emerging technologies, market opportunities, and competitive dynamics. Source high-potential AI startups for acquisition, investment, or partnership, and build a strong presence across the founder and VC ecosystem through meetups, conferences, and events. Drive workstreams across diligence, valuation, financial modeling, strategic assessment, and internal recommendations. Partner with Product and Engineering leaders to evaluate build/buy/partner opportunities aligned with Datadog's AI roadmap. Support negotiation processes, including term sheets and partnership structures, and collaborate on integration planning with cross-functional partners after deals close. Help attract early-stage AI companies into Datadog's startup program. Wh

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

We’re looking for an experienced sourcing leader to join the Datadog Procurement team and help grow the Strategic Sourcing group. Make an impact by partnering closely with senior technology and business leaders, owning our fastest-growing AI, neocloud, and inference spend end-to-end, and continuing to prove the value that Strategic Sourcing brings to the organization. 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 AI spend category end-to-end, covering foundation-model and AI APIs, AI development and productivity tools, and AI-enabled SaaS (with neocloud and inference compute as an emerging area), while developing and executing category strategies aligned to business objectives Champion AI and automation adoption across the sourcing function by identifying tools (e.g. Claude, ChatGPT) and building repeatable workflows that make sourcing faster, smarter, and more scalable Lead high-value AI vendor negotiations spanning foundation-model and API agreements, AI development and productivity tools, and AI SaaS, structuring seat- and consumption-based pricing across net-new purchases and strategic renewals, and building neocloud and GPU-capacity capability as the category grows Partner with Engineering and Finance to turn architectural and consumption trade-offs into commercial business cases, forecasts, and savings targets Build pricing and consumption models and apply FinOps discipline to quantify buying scenarios and uncover savings across a fast-moving spend base Work alongside executive and senior technology leadership as a trusted advisor on AI and neocloud investment decisions, influencing strategy and commercial trade-offs at the leadership level Track category KPIs (savings, pipeline, cycle time), monitor AI market, vendor, and pricing trends,

About the team The Applied AI Engineer, Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships wi

Databases and data stores are at the center of our applications, for legacy applications and modern AI applications alike. Yet most observability and optimization approaches lack a holistic approach or application context. Datadog has been on a mission to revolutionize how databases are operated, flipping what is often seen as a black box of complexity prone to security and performance risks, into a well oiled machine enabling our builders and businesses to move faster and smarter. We’re looking for an experienced product manager passionate about joining this mission to lead this product opportunity. 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 ambitious investments that rethink how customers operate and get value from their databases, diving into ambiguity, working with our customers on new models, and shipping new products and changes to existing products. Develop a deep understanding of our customers and their issues, what problems are really behind those issues, and how we can improve how databases are operationalized across SRE teams, DBAs and application developers. Continuously refine your understanding of database management systems and datastores from SQL and OLTP based to NoSQL e.g. AWS RDS, PostgreSQL, SQL Server, MongoDB, MySQL, etc Define, build and launch the next generation of database monitoring and optimization capabilities for our customers Join a talented engineering team with a record of disrupting observability approaches to further the mission of demystifying and optimizing databases using your team’s creativity, alongside your customers’ problems, as a key resource. Collaborate with other Product teams in Datadog to maintain and improve all Datadog products, improve the seamless integration across th

About the Team DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. The Marketing Technology team is responsible for delivering best-in-class tools, data, and processes so teams at DoorDash can effectively acquire new customers, drive retention, and grow new business lines across all our audiences. Our mission is to enable teams to deliver personalized, engaging, and relevant content across all our owned and paid channels. We partner closely with Product, Engineering, Data Science, and Analytics teams to translate Marketing’s technology needs into measurable business outcomes for our Growth and Performance Marketing teams. About the Role We're looking for a Senior Associate, AI Solutions Architect to help build and scale AI-powered tools across DoorDash's Marketing teams. You'll work alongside our existing Marketing Technology AI Solutions Architects to identify opportunities where AI can solve real marketing problems, then build, test, and iterate on the solutions that make it happen. This role is grounded in hands-on building: you'll spend your time prototyping, coding, and shipping tools rather than pitching strategy from the sidelines. This is a great opportunity to grow your technical and strategic skills at the intersection of marketing and AI. You'll get mentorship from a team of builders and exposure to the full lifecycle of AI development from prototype to deployment. This role will report to the Senior Manager, Marketing Technology within the Growth Marketing organization. You're excited about this opportunity because you will… Build and deploy AI-powered tools and automations, such as automated reporting, QA frameworks, and workflow optimizations. Develop MVPs and proof-of-concepts, then iterate based on user feedback within a defined w

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Product at Brex The Product team is at the forefront of Brex's mission to empower employees anywhere to make better financial decisions. With a deep understanding of the business, we identify and scope out the most impactful opportunities for Brex to tackle. We are responsible for aligning cross-functional teams — such as Engineering, Legal, Compliance, and Design — on key decisions. We set strategy and drive products from inception to launch, enabling Brex to grow rapidly and help our customers reach their full potential. Unlocking AI Agents for the Finance Admin Companies buy Brex to run their spend, and the person on the hook for that is the finance admin — a controller, an accounting manager, a finance ops lead. Their job comes down to two things they can never quite get ahead of: making sure money is being spent compliantly and documented in time to close the books, and knowing where the company's money is actually going. Today t

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. Responsibilities: Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality Building and maintaining automated pipelines that will enforce the correctness of code examp

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Why join us Brex is the AI-powered spend platform. We help companies spend with confidence with integrated corporate cards, banking, and global payments, plus intuitive software for travel and expenses. Tens of thousands of companies from startups to enterprises — including DoorDash, Flexport, and Compass — use Brex to proactively control spend, reduce costs, and increase efficiency on a global scale. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We're committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT,

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Engineering at Brex Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders. What you’ll do As a Staff Software Engineer in Banking, you will help shape the technical direction of one of Brex’s most strategic and complex product areas. The Banking org is both a product and platform org, it owns the Brex Business Account product and AP offerings like Bill Pay and Vendors, and the underlying money movement platform and partner integrations that power those experiences. In this role, you’ll work across customer-facing product surfaces and core financial infrastructure, driving architecture, reliability, and

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for engineers with deep AI/ML and low-level systems experience who want to build the best technical support experience in the world. This isn't a traditional support role — it's an engineering role where you happen to be closest to our customers. You'll split your time roughly 50/50 between working directly with customers and shipping fixes, features, and automation that improve Modal for everyone. When you help a customer debug a training run, you'll also fix the underlying issue in the platform. When you notice ten customers hitting the same friction point, you'll build the tooling or automation that eliminates it entirely. This role is for people who solve problems, not people who answer tickets. The problems you encounter are deeply technical and arise from running some of the most demanding AI workloads in the world. You'll be a member of our eng

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

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 You will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the Financial Services vertical, partnering with banks, asset managers, and private capital investors to deploy next-generation AI capabilities across their operations, investment processes, and portfolio companies. You will own delivery end-to-end: embedding with Financial Services customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in New York City. We use a hybrid work model of 3 days in the office per w

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.