Ai Developer in New York

We are looking for a talented engineer to lead evaluation of startup acquisition opportunities in the AI, cloud and security space. You will drive product evaluations, prepare and manage technical architecture discussions with target groups in Product and Engineering and provide roadmap suggestions for M&A and investments for Datadog. You will be a key partner to Datadog’s C-level leadership and highly visible at the most senior levels of Datadog. The role is reporting into the Senior Director of Product Strategy and falls within the Product organization. We are looking for an innovative and strategic thinker who is passionate about the latest tech being developed by startups in the cloud, AI and security space. The ideal candidate enjoys researching and evaluating new technologies, works effectively with cross-functional teams, and communicates opinions concisely to our leadership team. Broad understanding of relevant Cloud Technologies and deep understanding of the full coverage of Datadogs current offerings is necessary. The Corporate Development team is small and values authentic, strong-willed individuals who think creatively and proactively. This role leads technical due diligence from a product and architecture perspective across our acquisition pipeline. You'll scope and stand up proof-of-concept and sandbox environments to stress-test candidate products, then give an honest, unvarnished view of their quality and depth - the kind of assessment that holds up regardless of deal momentum. You'll assess technical architecture, flag the risks and open questions that matter most early, and turn that into a clear post-acquisition integration path. Working closely with engineering, you'll keep the evaluation focused on what's actually decision-relevant, then translate the findings into strategic recommendations for leadership and help carry the integration through by partnering with the right people on the other side. What You’l

About Us Small businesses are the backbone of the US economy, comprising almost half of the GDP and the private workforce. Yet, big banks don’t provide the access, assistance and modern tools that owners need to successfully grow their business. We started Novo to challenge the status quo—we’re on a mission to increase the GDP of the modern entrepreneur by creating the go-to banking platform for small businesses (SMBs). Novo is flipping the script of the banking world, and we’re excited to lead the small business banking revolution. At Novo, we’re here to help entrepreneurs, freelancers, startups and SMBs achieve their financial goals by empowering them with an operating system that makes business banking as easy as iOS. We developed modern bank accounts and tools to help to save time and increase cash flow. Our unique product integrations enable easy access to tracking payments, transferring money internationally, managing business transactions and more. We’ve made a big impact in a short amount of time, helping thousands of organizations access powerfully simple business banking. Why Novo? • Novo is a rapidly growing series B fintech startup with a mission-driven team that’s passionate about helping every small business in America • Positive, inclusive, supportive culture cheering you on your journey • We work with very new technologies and architecture patterns • Offices in NYC and India Role Summary The Senior Manager, Customer Support & Success is the strategic owner of Novo's most critical 1:1 customer touchpoints - from complex escalations and collections recovery to a proactive customer success motion you’ll get to build from scratch. This is a player-coach role: you will lead a small, high-performing team while staying close to the work yourself. You will operate with significant autonomy, bring consistency and customer obsession, and shape what this function looks like two to three years from now. About the Role Escalations & Collections — Raise th

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Chan Zuckerberg Biohub New York is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Biohub itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and persp

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,

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

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

Become a part of our caring community Help shape practical, responsible AI solutions that improve healthcare experiences and outcomes. Humana’s Enterprise AI organization develops safe, scalable AI solutions across our Insurance and CenterWell businesses. We bring together product managers, data scientists, engineers, policy experts, and business leaders to apply emerging technology to meaningful healthcare challenges. As Associate Director of Applied AI, you will lead teams that design, build, and deploy enterprise AI solutions, with a focus on generative AI and intelligent agents. You will connect technical strategy to business needs, guide responsible delivery in a regulated environment, and help teams turn promising ideas into measurable outcomes for members, patients, and associates. Key Responsibilities Lead and mentor teams developing production-ready AI solutions that improve healthcare delivery, member experiences, and business operations. Help define and execute the roadmap for applied AI initiatives in alignment with enterprise priorities and business needs. Guide the evaluation and adoption of machine learning, generative AI, large language models, multimodal models, and intelligent agent technologies. Oversee scalable APIs, frameworks, data pipelines, retrieval-augmented generation solutions, and agent orchestration capabilities. Partner with product, data science, engineering, architecture, security, and business teams to translate requirements into reliable solutions. Establish standards for AI evaluation, obse

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

Code Intelligence sits at the intersection of agentic engineering and product, running agents against real customer source code in production. This is a chance to own an AI-native team at the center of a business-critical growth area. High visibility, high leverage, and squarely in the fastest-growing part of the AI agent space. 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 employees can create a work-life harmony that best fits them. What You'll Do: Lead and develop an existing engineering team, building trust, setting technical direction, and establishing a high bar for ownership and execution. Own the roadmap and execution across four areas: source code indexing, PR Agentic Reviewers (agents that generate artifacts like metric descriptions on customer pull requests), shift-left work (extending code-writing agents to make direct changes to customer repos), and closed-loop feedback and evaluation systems including LLM-as-judge. Set the team's product strategy independently while partnering day-to-day with product teams company-wide — this team functions as its own product org. Build and operate scaled LLM and agent software in production: LLM APIs, agent frameworks, harness and tool-use layers, prompt and eval tooling, and closed-loop evaluation systems that measure and improve agent output quality. Partner closely with customers and internal stakeholders to deeply understand needs and translate them into technical direction. Drive the team's AI-native development practices, setting high standards for safety, validation, and increasing agent autonomy over time. Who You Are: Experienced engineering manager with a track record of shipping products with direct customer interaction, not just internal stakeholders. Hands-on experience building scaled LLM software: LLM APIs, agent frameworks, prompt and eval tooling, h

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: We’re seeking an experienced User Researcher to shape growth-related product decisions by delivering insights that fuel AI experiences. This role blends traditional growth research, such as adoption, monetization, and pricing and packaging, with fast-evolving AI features like Notion Agent and Chat that permeate experiences like onboarding and Workspace creation. It requires a unique mix of user research expertise, strategic foresight, and technical fluency in AI and AI product development. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Design and execute studies that evaluate how people experience Notion with AI in the loop, including how users discover, trust, and get value from AI, and identify barriers to adoption and willingness to pay. Run mixed-methods research (qual + quant), including interviews, concept testing, prototype/usability testing, diary

As a Cloud Security Engineer you will partner with different stakeholders across the organization to secure our cloud infrastructure. As part of the Platform Security organization we secure the building blocks of Datadog’s applications and infrastructure. We do this by building solutions to solve systemic risks and combine an approach of making the secure path easier and the insecure path harder to secure and accelerate the business. We regularly partner with the most bleeding edge internal products and are working to solve and build solutions to enable our safe usage of AI. We also develop AI based solutions to enable security at scale. We are looking for a Service Mesh and Kubernetes focused security specialist to help round out an incredibly strong infrastructure security focused group. You will rotate through a variety of internal projects and gain deep exposure to Datadog’s infrastructure. 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: Solve our most challenging cloud infrastructure security problems starting with our core building blocks and golden paths. Enable our engineers to build and ship secure solutions quickly. Build and extend Datadog’s Platform Security solutions. Leverage and influence the direction of Datadog’s products to secure our infrastructure, and provide internal feedback that enables our teams to improve the products for ourselves and our customers. Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent professional experience. Passionate about advocating for and implementing solutions to complex problems, at-scale, in a large multi-cloud environment. You don’t want to just provide security recommendations, you want to help imple

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 Role As Enterprise Sales Manager, Banking, you will build and lead a team of Account Directors focused on driving strategic growth across the world’s largest banking institutions. You’ll be a hands-on front-line leader responsible for helping your team navigate complex enterprise sales cycles, deepen executive relationships, and drive adoption of OpenAI’s platform across highly regulated banking environments. This role will shape how OpenAI partners with global banks as they rethink productivity, operations, customer engagement, risk management, and software development through AI. You will help define the GTM strategy, operating model, and industry playbook for one of OpenAI’s most strategic verticals. Key Responsibilities Recruit, develop, and lead a high-performing team of Account Directors focused on large enterprise banking institutions across North America. Create a strong coaching culture with frequent deal reviews, account strategy sessions, ride-alongs, and structured 1:1s that elevate team performance. Define and refine the GTM strategy for banking, including account prioritization, executive engagement strategy, and territory planning. Drive disciplined pipeline generation, forecasting accuracy, and operational rigor across a complex enterprise sales motion. Guide teams through highly consultative, multi-stakeholder opportunities involving technology, security, compliance, legal, and procurement stakeholders. Help customers translate AI and API capabilities into measurable business outcomes across banking use cases such as employee productivity, customer operations, risk and compliance, software engineering, knowledge management, and workflow automation. Lead teams selling into highly regulated environments with a deep understanding of banking-specific risk, governance, and data security considerations. Partner closely with Product, Solutions Architecture, Technical Success, Legal, Security, and Finance to help customers successfully deploy AI a

ROLE SUMMARY The Clinician Medical Monitor is accountable for providing medical and scientific expertise and oversight for Clinical Trials and serves as a single point of accountability for design, execution, monitoring, delivery and reporting of one or more clinical studies and to ensure patient safety. The clinician medical monitor may be required to design a development strategy for multiple protocols designed to obtain worldwide approval for a compound or group of compounds. In addition to study level activities, the clinician medical monitor may participate in standing committees, review compounds for potential in-licensing, including performance of due diligence reviews, and aid new business development on market opportunities and the target product profile. ROLE RESPONSIBILITIES Accountable for safety across the study Provide study team with medical advice for all medical issues during risk assessment and mitigation planning to enable quality, compliance and patient safety at the trial, site and patient level. Ensures development of and adherence to the Safety Surveillance Review Plan (SSRP). Consistent with the SSRP, performs and documents regular review of individual subject safety data, and performs review of cumulative safety data with the safety risk lead. As appropriate, the clinician medical monitor may delegate these responsibilities to the study clinician scientist identified in the SSRP. The specific components of safety data review are detailed in the appropriate SOPs and the “Safety Data Review Guide – for Clinicians.” Monitor study safety issues and provide input to serious adverse events (SAEs) reports. Provides appropriate medical context in terms of risk factors, medical history and other important medical factors required to put the SAE or AE into appropriate medical context required for benefit-risk assessm

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Addepar is looking for a high-energy, results-driven Business Development Representative to join our Business Development & Sales organization. Working very closely with Sales and key partners, BDRs are tasked with strategically developing and qualifying revenue opportunities within assigned account territories and segments. This is an exciting opportunity to generate and hunt for new business opportunities to fuel our growth across the wealth management, family office, private banking, and global investment management market segments. The ideal candidate will be passionate about finance and disruptive technology; have a sound eye for business and natural sales instincts; and be an eager, highly motivated, and tenacious self-starter. Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B , F-1 /OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment. What You’ll Do Generate new business opportunities to fuel Addepar’s growth Create and prioritize strategic target account lists and account attack plans within a defined territory Research and build new account