Sourcer in New York

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

Become a part of our caring community Every large organization is making critical decisions today about how it will leverage AI over the next decade. Few have leaders who can both define that vision and demonstrate its viability through hands-on engineering. This role requires both. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations to source documents, and route difficult cases to human experts. These capabilities support decisions that impact real healthcare outcomes for members. As a Principal AI Applied Engineer, you will define the technical strategy, architectural standards, and long-term vision for AI-enabled products across the organization. You will influence enterprise-wide decisions regarding AI platforms, model strategies, engineering standards, and technology investments while remaining deeply hands-on in prototyping, experimentation, architecture, and software development. This is the highest-level individual contributor role within the AI Applied Engineering organization. Success requires exceptional technical depth, organizational influence, strategic thinking, and the ability to translate emerging AI capabilities into scalable, reliable, and responsible production systems. Why Join Us Shape the long-term AI architecture and engineering direction for a large enterprise healthcare organization. Influence how AI-enabled products are designed, built, evaluated, deployed, and governed across multiple teams. Drive strategic decisions involving models, vendors, platforms, infrastructure, and shared capabilities. Prototype and validate emerging technologies before the organization invests at scale.</

This Engineering Manager will lead the Data Visualizations Explorations team within the Graphing organization, setting product direction, and coaching and developing team members. They will staff and drive projects that build end to end experiences for Datadog’s core users: observability engineers. This includes extending the capabilities of core widgets like Hostmap and Geomap Visualizations and finding innovative ways to leverage existing Datadog data sources. This role also involves close partnerships with other product teams to deeply understand customer needs and deliver compelling data 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 Data Visualization Explorations 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. Proactively anticipate cross-team dependencies and blockers to goals. Identify opportunities to appropriately reuse or customize features across dashboards, notebooks, and product pages. Deeply understand the needs of our customers and other Datadog products we work with. Participate in customer conversations, review product briefs, read feature requests, and coach team members to adopt these practices as well. Define and maintain high standards for operations practices, including bug triage and remediation, incident response, and gathering and analyzing performance telemetry for our widgets. Who You Are: At least 2 years of people management experience in a software engineering or similar setting Strong TypeScript/JavaScript skills, including familiarity with front

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

Datadog’s Implementation Services team helps customers implement and deploy Datadog quickly and successfully. Our team of architects leads the discovery, design, build, and launch of the Datadog platform to help customers accelerate time to value and get the most out of their investment. As a Senior Services Architect focused on Security and Cloud SIEM, you will help customers design, implement, and operationalize Datadog’s security capabilities across cloud, infrastructure, application, and log data sources. You will lead structured, outcome-driven professional services engagements delivered through a day-based professional services delivery model, partnering directly with customers through co-development working sessions, architecture workshops, implementation planning, and operational handoff. This role is ideal for someone who combines customer-facing consulting experience with strong cybersecurity knowledge, hands-on Cloud SIEM implementation skills, and an understanding of security control frameworks such as NIST 800-53, the NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. 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: Design and guide execution of Datadog implementations, focusing on Security and Cloud SIEM deployment, including discovery, requirements gathering, technical architecture, deployment planning, and launch. Partner with customers to map security requirements, controls, and monitoring objectives to Datadog capabilities, including frameworks such as NIST 800-53, NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. Advise customers on security data strategy, including log source prioritization, parsing, normalizat

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

Datadog is looking for a driven, entrepreneurial Customer Marketing Manager to join our Corporate Marketing team — a group of talented professionals responsible for sourcing, creating, and amplifying stories of customers who are achieving meaningful technology and business outcomes with Datadog. This role is designed for marketers who thrive in dynamic environments, are passionate about building genuine customer relationships, and know how to turn great stories into compelling, data-driven programs. 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: Source and track opportunities to promote customer wins by working with cross-functional partners across product marketing, partner marketing, sales, customer success, marketing operations, demand generation, and more Track and report on program performance, including participation rates, customer reception, content output, and influenced pipeline and closed deals Build a portfolio of customer advocates through online and in-person engagements to source strong stories and promotional opportunities Interview customers and product leaders — in-person and on camera — to produce customer marketing assets, like case studies, video testimonials, promotional quotes, and slides Design, deliver, and continuously optimize programs and incentive strategies that attract customers to participate in advocacy activities Lead programs that drive high-quality customer reviews to peer review sites such as Gartner Peer Insights, G2, and TrustRadius Influence how the broader team operates by modeling best practices, championing process improvements, and driving adoption of AI tools and cross-team efficiencies Who You Are: You have 4+ years of experience in customer marketing and/or advocacy for a B2B technology company

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. CLEAR1 is CLEAR's B2B identity verification business, serving enterprise, healthcare, and workforce customers through direct sales and partners. We are growing fast and need a Revenue Operations Leader who can build the operating model to match. This is a strategy and accountability role. You will own how the go-to-market team plans, measures, forecasts, and runs its process across the full customer lifecycle, from first touch through renewal and expansion. You will define what our revenue numbers mean and where they come from, make them consistent from rep to Board, and hold the team to the process that produces them. You will be the CRO's partner on where to invest and what is working. You have done this before at a growth-stage B2B company, you think like a finance partner as much as an operator, and you direct systems work without needing to do it yourself. What you'll do: Own CLEAR1’s revenue operating model, partnering with the CRO and Finance on annual and quarterly planning across capacity, quotas, coverage, pipeline targets, and investment decisions Establish a single source of truth for revenue performance by defining core metrics, data sources, and reporting across ARR, net new ARR, GRR, NRR, pipeline coverage, win rate, sales cycle, and CAC payback; own executive and Board-level reporting Lead forecasting and revenue accountability end to end across new business, renewals, and expansion, establishing clear definitions, cadence, and ownership while continuously improving forecast accuracy Build and enforce scalable processes

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 Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence— you will uncover insights about markets and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a Macro Analyst, Market Intelligence covering the US, you will work with alternative data to gather macroeconomic context and identify insights relevant to rates and FX markets. You will then partner with our team of data scientists and engineers to develop analyses that you deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the markets within your assigned coverage Produce research for internal consumption by our investment professionals across a variety of channels, including written reports, verbal communication, data feeds, and visualizations Interact directly with our investment professionals to learn the macro investment process from them and help drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, evaluate, and draw value from new and existing data assets to produce actionable research for investment professionals WHAT’S REQUIRED &nb

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: 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. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it’s more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using financial data. Our work is ingrained in Brex’s decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our consumers. What you’ll do This position is on our Data Enablement Platform team. The Brex product requires a huge amount of data to power our client experiences. With a largely async architecture, proliferation of services and multiple operations systems, this data originates from many different sources and in different forms. To ensure that our product experience is unbounded in how it leverages this data, the Data Enablement Platform team owns and operates the systems required to deliver it t

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a Senior Manager of Industrial Engineering to join CLEAR's Central Operations team. This role is the quantitative backbone of our Experience & Operations Design function — owning the data-driven design standards, labor models, and capacity planning that determine how CLEAR's physical operation is structured and staffed. You will be the analytical engine behind lane design decisions, engineered labor standards, and demand forecasts, ensuring the operation is designed to deliver a consistently excellent member experience efficiently at scale. What you'll do: Develop and own engineered labor standards and staffing models across CLEAR’s physical experiences, including Verifier, Greeter, eGate, Concierge, TSA PreCheck, Enrollment, Sports, and new programs, serving as the operations source of truth for labor and headcount inputs Define physical operating requirements and sizing standards across lane configurations, verification and enrollment experiences, hardware placement, and queue management; lead checkpoint design for new and existing airport locations Lead demand forecasting and capacity planning across CLEAR experiences, modeling throughput, staffing requirements, operating hours, and operational impact for new programs, launches, surge periods, and events Drive operational efficiency through time studies, process analysis, and labor optimization, identifying and developing opportunities to improve productivity, capacity, and the Member experience across the network Partner cross-functionally with Operations,