Go To Market Engineer in New York

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

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. About Talent at Modal Modal is growing fast, and the programs that bring people in and set them up to succeed are still being built. You'll join the Talent team as one of its first hires focused purely on programs; working closely with recruiting and leadership to build the events, internship, and campus presence that shape how the best people discover and experience Modal for the first time. The Role As Talent Programs Manager, you will own Modal's talent events, our intern program, and our presence at career fairs, end-to-end. This is a build-from-the-ground-up role for someone who wants full ownership rather than an existing playbook to execute. You'll work directly with recruiters, hiring managers, and marketing to make sure every program ladders up to real hiring outcomes, and you'll be the person who makes candidates' and interns' first experience of Modal a great one.

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

As a Corporate Communication Senior Manager focused on Executive Communications Programs, you will build and scale Datadog's integrated thought leadership program — spanning executive communications, earned and owned channels, and events — with a focus on extending it across priority regions. This role sits at the intersection of strategy and execution: you'll translate leadership priorities into playbooks, frameworks, and measurable programs, then run them day to day. Success hinges on connecting dots across initiatives and partner teams to find new opportunities to tell Datadog's story through our executive voices. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Partner with the Global Head of Corporate Comms to develop and execute an integrated thought leadership program with clear objectives and measurable outcomes. Build the operating framework behind the program — playbooks, cross-team coordination models, and repeatable processes that let it scale across regions. Identify opportunities to put Datadog thought leaders in front of the right audiences, including vetting speaking engagements: where we need to be, what we should be saying, and which channel (social, traditional media, stage) delivers the most impact. Work with US Comms and Social leads to augment existing campaigns and build evergreen thought leadership programs across channels. Partner with Field Marketing on event strategy and execution, with a focus on advancing our key narratives around AI and security. Develop strategic messaging for senior executives across key business moments — corporate announcements, company milestones, and other high-priority communications. Serve as the Corporate Comms "captain": keep a bird's-eye view of initiatives across the company, manage day-to-day coo

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 business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: Drive in-depth quantitative analyses to inform our pricing and packaging strategy. Help spin up our deal desk and streamline enterprise deals. Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. Implement new tools and processes to enable the GTM org to grow rapidly. Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. Requirements: We are looking

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 hiring a Compute Strategy and Operations lead to own how Modal plans for and acquires GPU and CPU capacity. You'll size our infrastructure needs ahead of demand, source supply across hyperscalers, neoclouds, and datacenter operators, and negotiate and close the contracts to secure it. The compute you secure directly determines what Modal can sell and build. In this role, you will: Own end-to-end procurement of GPU and CPU capacity across hyperscalers, neoclouds, and datacenter operators Build and maintain a strong pipeline of supplier relationships Evaluate supply options on price, availability, hardware specs, networking capabilities, and SLA terms Negotiate and close contracts: reserved capacity agreements, spot arrangements, MSAs, DPAs, and order forms Work closely with our engineering teams to translate technical requirements into procurement specs Track

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 Forward Deployed ML Engineers who want to work at the intersection of deep technical work and direct customer impact. As an ML FDE, you'll partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on their most demanding workloads — LLM serving, model training (SFT, RLHF), audio pipelines, scientific computing, and more. You're helping teams reach outcomes most engineers can't on their own. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the AI stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads

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

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 a People Operations Generalist to join our growing People team. You'll touch the employee lifecycle end-to-end — from offer acceptance through offboarding — while helping to build the processes and documentation that let our People function scale with the business. This is a great fit for a highly organized, systems-oriented people person who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. What you’ll do Own and continuously improve the new hire onboarding experience, ensuring employees are set up for success and internal tasks are tracked and completed on time. Serve as a first point of contact for employee questions across the full HR spectrum, triaging and routing more complex issues to the right People team member or external partner. Maintain and improve self-service resources (FAQs, Not

Datadog's brand is entering a new chapter—one that needs a designer with the taste and craft to set the bar for what it looks and feels like. We're looking for a Lead Designer to support that evolution: someone who can take a brief, create visionary concepts, pitch them with conviction, and then build the system that lets the team anchor and scale the direction. This role shapes how our brand shows up everywhere it counts and enables brand scalability across every customer touchpoint, from campaigns and events to digital experiences. This is a hands-on craft role first. You'll bring deep expertise in design, brand identity, visual language, and systems thinking, paired with strategic thinking, business-problem-solving approach. You're as comfortable concepting a bold campaign idea as you are building the design system that makes it repeatable. You move with ease across mediums and you bring a team-oriented, can-do attitude to whatever the work requires. You bring hands-on experience using AI-assisted workflows to elevate how we design, build, and scale our brand. You'll combine exceptional brand craft with a passion for building enduring systems, enabling teams across the organization to create with confidence through thoughtful tools, documentation, and design leadership. 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 evolution of Datadog’s visual identity and establish the quality bar for brand expression across every touchpoint. Build the brand systems, templates, asset libraries, and guidelines that allow teams across Datadog to create high-quality work quickly. Design, build, and steward a scalable, Figma-native brand system—including component libraries, variables, documentation, and governance—that enables consistency across a grow

We are the Experimentation team at Datadog, a startup operating inside one of the fastest-growing companies in software. The team brings together engineers who joined through Datadog’s May 2025 acquisition of Eppo with engineers from across Datadog, and together we are building feature flagging and experimentation into the platform. Both products were recently launched this year, and we are just getting started: we are migrating customers from Eppo onto Datadog while shipping an ambitious roadmap across both flagging and experimentation. Our statistics engineers hold PhDs and are pushing the boundaries of what an experimentation platform can do. Our full-stack engineers move fast, lean on the latest AI tooling, and prototype and ship new features weekly. We talk to customers directly to shape requirements, and our roadmap is driven by our own product vision and sharpened by real customer and sales input. We are looking for an Engineering Manager to lead the team building the Experimentation App. You will own one to two squads to start, partnering closely with our engineers, statisticians, product managers, and designers to turn a deep roadmap into a shipped product. To conform to US export control regulations, candidates should be eligible for any required authorizations from the US government. What You’ll Do: Lead, mentor, and grow a team of strong full-stack and frontend engineers. Help them grow to the next level and continuously provide them opportunities to develop. Own delivery for the Experimentation App from planning through production, balancing speed with quality in a fast-paced environment. Set technical direction in partnership with your team and our statistics engineers, engaging credibly on architecture and tradeoffs. Partner with Product, Design, and customers directly to shape requirements and turn customer and sales input into roadmap. Foster a culture of fast iteration and high engineering standards through code reviews, design reviews, and blamele

The GTM Operations Associate - Channels & Alliances will join a global team driving Datadog's next phase of growth. We are interdisciplinary thinkers with diverse backgrounds across consulting, finance, strategy, operations, and technology. Our team partners directly with GTM leaders to improve operational efficiency, support data-driven decision-making, and scale the processes and systems that enable continued growth. In this role, you will serve as an operational partner to Datadog's Channels & Alliances organization. You will execute critical business operations, support reporting and business systems, and help scale operational processes across the organization. You will work closely with cross-functional teams to ensure our C&A teams have the tools, data, and operational support they need to be successful. Success in this role requires strong attention to detail, systems thinking, and a passion for improving how teams operate. 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 recurring operational processes that support the global Channels & Alliances organization, ensuring execution is timely, accurate, and scalable. Build, maintain, and enhance Salesforce reports and dashboards to provide visibility into pipeline, partner performance, and other key business metrics. Partner with C&A, Revenue Operations, Systems, Sales, and other cross-functional teams to improve operational workflows, resolve business issues, and ensure data integrity across systems. Coordinate with and evaluate external vendors to support operational processes, systems enhancements, and business initiatives. Create and maintain process documentation, playbooks, and standard operating procedures to improve consistency and scalability across the organization.

Manager I, Engineering - Onboarding Growth This Engineering Manager will lead the Onboarding team within the Shared Capabilities organization, setting product direction, and coaching and developing team members. They will staff and drive projects that drive new users to adopt Datadog in their organizations. From the first time a new user signs up for a Datadog trial, this team is responsible for making sure they have a world class setup and onboarding experience, and can realize the full value of Datadog in their organization. Onboarding owns the “front door” of Datadog, the very first experience new users and prospective customers encounter. This work is extremely important to company success - improving our onboarding process directly impacts new users ability to find value with Datadog quickly. This role also involves close partnerships with other product teams to deeply understand customer needs and deliver compelling first-time user experiences 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: Work with Product Management and Design to plan and staff projects for the Onboarding Growth team Coach and develop engineers at various levels Ensure strong cross-team communication and design best practices around project management, code review, architecture patterns, and more Build UX features to streamline the onboarding and trial experience through rapid experimentation Build out data platforms and use that data to personalize the onboarding experience for each user Work directly with product teams to ensure each product has a best in class new user experience Create AI-assisted setup options to make sure initial setup “just works” out of the box Champion the use of analytics data to analyze user behaviour and apply those insights

Datadog is entering a new chapter in how our product looks, feels, and operates. Our Design Lab is defining a new visual direction for the platform, and we’re looking for a Senior Staff Visual Product Designer to help turn that direction into a coherent product experience. Datadog is dense, technical, and used by people working through complex problems—often under real pressure. The challenge is not simply applying a new aesthetic. It is rethinking hierarchy, layout, navigation, interaction, and product patterns so the experience becomes clearer, more cohesive, and more expressive without losing the power our users rely on. This is a hands-on product design leadership role for someone who combines strong visual judgment with deep product and systems thinking. You’ll work alongside visual designers, motion designers, product designers, Design Systems, and Engineering to ensure the new direction changes how Datadog works—not just how it looks. What You'll Do Co-develop Datadog’s next visual direction by applying and stress-testing it across representative product journeys. Translate visual principles into concrete decisions about hierarchy, layout, navigation, information architecture, interaction, and behavior. Use visual language to clarify complex, data-dense experiences — hierarchy, density, and attention. Hold the visual quality bar across work you don't own, and align teams around it. Prototype, test, and refine new patterns before they become systemized. Partner deeply with Product Design, Design Systems, and engineering to turn successful concepts into durable system guidance and implementation. Create clear artifacts, pilots, and narratives that help teams adopt the direction and raise the product quality bar. Influence stakeholders across design, engineering, product, and executive partners. You will report directly to the Design Director and work as part of a small, focused team defining the future state before it scales across hundreds

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