Codex Deployment Engineer in New York

About OpenAI OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We build models and products that help people learn, create, and solve problems—and we work to do so safely and responsibly. About the Team OpenAI’s products are talked about by people, not just press and pundits. More than 900 million people use our tools each week, learning from one other and passing along what works. Their stories shape our reputation and encourage others to try our products. Our community team builds direct relationships & channels with people who use our tech then amplifies their stories and use cases so peers can learn from them and channels their insights to our product and research teams. About the Role We are seeking an exceptional Technical Community Program Manager to help manage and scale a high-signal community of advanced ChatGPT Pro users. This is a hands-on, technically fluent role at the intersection of community-building, product enablement, user research, product education, and editorial storytelling. You do not need to be a full-time software engineer, but you should be comfortable understanding technical workflows, asking sharp technical questions, using the latest AI tools, and helping advanced users explain what they are building. You will report to the Head of Pro Subscriber Community and will be based in New York City. In this role, you will: Run and grow a high-signal community Help manage and deepen engagement with the ChatGPT Pro cohort of advanced users across disciplines Design and execute high-touch community programming, including product demos, office hours, show-and-tell sessions, peer-learning formats, and in-person events Build repeatable systems for onboarding, engagement, retention, and member communications Build deep relationships with exceptional users Identify, recruit, and onboard new individuals doing high-impact work with ChatGPT and Codex Conduct in-depth interviews and maintain ongoing r

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

We're on a mission to build the best platform in the world to defend the enterprise from code-to-cloud-to-runtime. Used by thousands of companies globally, Datadog security products uniquely leverage Datadog’s unified security and observability platform so Security, DevOps and SRE can collaborate rapidly and seamlessly to deliver better detection, prioritization and remediation. Our product and engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. In this competitive market, the Group Product Manager for Code Security will play a mission-critical role in providing product and strategy leadership to grow Datadog’s market share through differentiation, innovation and compelling customer value. This leader will lead a talented and growing team of product managers and work with world class engineers to build and grow multiple Code Security products that play an essential role for our customers’ code security programs, and growing Datadog into a security industry leader. 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: Run and grow multiple Code Security products to meet revenue and business targets with the goal of building a multi-hundred million dollar annual business. Lead and own product strategy and roadmap for accountable security products, fully aligned to revenue and business goals and with compelling differentiation and customer value. Ensure predictable roadmap execution across direct and partner teams to achieve product and business outcomes required to meet the revenue and business goals. Analyze and develop pricing and packaging strategies to maximize revenue through attaching deep understanding of market dynamics and other strategic leverage points. Drive GTM strategy with GTM partner teams

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 in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

The way products get built is changing. Agents write a growing share of shipped interfaces, designers work in code, and a design system's output is bigger than a component library. At Datadog we're redefining ours for that world, and evolving how the product looks and feels at the same time. DRUIDS is the design system behind every Datadog surface, used daily by more than a hundred designers and thousands of engineers across thirty-plus products. You'll lead the team that owns it: designers and design engineers who set the system's direction, hold the quality bar for what ships, and build the tools that make designing in code the default way to work. The team partners closely with product designers, frontend engineers and PMs across the company. This is a hands-on leadership role in a technical, engineering-forward company. You'll be expected to have a point of view and defend it, to be the person the design org asks about quality, and to make the call when work isn't good enough yet. Much of what a design system should be right now hasn't been settled — here or anywhere else. If you're a designer who never stopped making things, and you'd rather decide what a system should be than maintain one that already exists, this is the role. 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 team and set its direction Decide what DRUIDS owns, what it ships, and what stays with product teams. Own where the system goes next. Have a view on what a design system should be, and argue for it. Turn direction into a roadmap, and work with partners on what gets built and when. Coach the designers and design engineers on your team, be clear about what each person owns, and hire as the team grows. Own craft and quality Own the craft and quality of components, patterns,

As a Product Manager – IaC Detection, you will define, build, and launch capabilities that proactively detect infrastructure issues in code (e.g. Terraform, Helm) before they can be deployed into production and escalate into production incidents. The Infrastructure Monitoring team has pioneered shift-left detection in the industry with Bits Infrastructure Operations , and we’re looking for a Product Manager to expand this capability to a broader set of use cases Customers (and thus developers) are increasingly standardizing on IaC tools to deploy and maintain ever-growing infrastructure in the cloud. At the same time, SREs and Infra teams struggle with an increasing number of production incidents. By shifting-left and identifying high-impact infra changes before they are deployed, we help reduce production incidents, reduce waste, and free up SRE time to focus on value-added tasks. You will own the roadmap to expand IaC detection to a broader set of use cases, including cost detection, blast radius impact, as well as configuration changes on infrastructure powering applications like nginx, postgres and more. You’ll partner closely with Engineering, Design, and customers to build and iterate on the roadmap, build product market fit, drive customer adoption (including internal usage), and focus on coverage and correctness of the AI system. This is an opportunity to lead an initiative at the intersection of AI, infrastructure operations, and autonomous observability. 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 product roadmap for IaC Detection, enabling customers to proactively detect and catch high-impact infrastructure and configuration changes before they are deployed into production and escalate into incidents. Define the end-to

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 builds AI infrastructure products that developers love. That's how we grew so quickly and why word-of-mouth remains one of our most important channels today. From powering one of the largest vibe-coding platforms at Lovable to enabling teams like Ramp to build their own internal coding agents , Modal Sandboxes are used by developers to safely execute AI-generated code at scale. We're now hiring our first developer relations engineer focused on Modal Sandboxes. Whether it’s banger tweets , in-depth technical resources or long-form talks , we want to meet developers by any medium necessary and empower them to build and ship novel AI products. In this role, you will primarily be creating and distributing technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcas

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at a high scale - trillions of data points per day — providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Opportunity We are looking for an experienced software engineer to join our CI/CD Security Team within our SDLC Security organization. We work at the intersection of security and engineering infrastructure to secure Datadog's continuous integration and continuous delivery systems. Our responsibilities include hardening pipelines, protecting credentials, and enforcing tightly scoped access controls. We also develop authorization and verification mechanisms to ensure that only trusted code and approved processes can reach production. In this role, you will shape and build a new security layer for our CI/CD infrastructure and drive its adoption across the engineering organization. You will solve challenging systems problems around trusted build provenance, secure secret delivery, and real-time policy enforcement at high throughput. The work sits directly in the critical path of software delivery, where strong security guarantees have to coexist with low latency, high reliability, and a seamless developer experience. You’ll join at an ideal time to make a big impact, as the need for robust software supply chain security is higher than ever. Datadog is growing rapidly, and AI-assisted development is increasing both the pace of software delivery and the amount of activity flowing through our CI/CD systems. Securing that scale without slowing engineers down requires strong software engineering fundamentals, thoughtful automation, and security controls designed to operate reliably at high throughput. At Datadog, we pla

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

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. 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 a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. 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: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer, Application Security you will be responsible for identifying and mitigating security vulnerabilities within software applications through building security tools, code reviews, penetration testing, and security assessments. We’re looking for people who will work closely with development teams to ensure secure coding practices are integrated throughout the software development lifecycle, preventing security risks before they emerge. You will also provide security guidance to developers and other stakeholders, fostering a culture of security awareness within the organization. The role is preferred to be based in San Francisco, Seattle or New York City but may consider remote work. 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: Perform Security Assessments : Conduct regular security assessments, code reviews, and penetration testing to identify vulnerabilities in applications and software. Develop and Implement Security Tools : Design, develop, and implement security tools, frameworks, and methodologies to protect applications against security threats. Collaborate with Development Teams : Work closely with development teams to ensure security best practices are integrated throughout the software development lifecycle (SDLC), including secure coding guidelines. Threat Modeling and Risk Assessment : Conduct threat modeling and risk

Our Mission You call. You wait. You call again. In every other part of your life, you book in seconds. In healthcare, you’re blocked. We’re here to give power to the patient. For nearly 20 years, we’ve built the leading healthcare marketplace - helping tens of millions of people find and book the care they need. Now, we’re going further: building our infrastructure beyond Zocdoc’s marketplace to power access to care wherever patients search, from provider websites and insurance directories to search engines, AI platforms, and more. Healthcare still lacks something every other major consumer industry takes for granted: a seamless way to go from seeking to getting . We don’t want to own the front door to care; there isn't one. We want to make sure all of those doors open when patients are knocking. Fixing healthcare starts with fixing access to it. And we're still just getting started. About the Role We're transforming how healthcare practices interact with Zocdoc, building intelligent systems that understand each practice's needs and guide them toward actions that grow their business. This means personalized homepages, smart recommendations, AI-assisted configuration, and workflows that make Zocdoc essential to daily operations. As Senior Software Engineer, you'll build these systems end-to-end. You'll own features from design through production, work across the stack, and collaborate with Product, Design, and Data Science to ship experiences that matter. What You'll Do Build platform components - including practice profile services, engagement scoring pipelines, recommendation APIs, personalization infrastructure. Ship product features end-to-end - database to API to front-end, owning the full lifecycle. Work with Data Science to integrate ML models build feature pipelines, call model endpoints, instrument feedback loops. Write production-ready code with strong testing, observability, and error handling. Participate in design discussio

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. As a Sales Engineer II, you will be responsible for ensuring our customers successfully integrate with the CLEAR1 platform, with a focus on our Healthcare vertical. You will work across the Growth, Product, and Engineering teams to develop a deep understanding of the problems our customers are facing and influence how we’re building our platform for scale. We’re looking for a candidate with an excellent technical background who is looking to have a direct impact on customer and developer experiences. What you'll do: Lead presales customer engagements, including technical discovery, product demos, use case demos, RFPs, solution and integration scoping, and proof-of-concepts Drive customer integration for enterprise-level customers including building reference applications, prototypes, and architecture diagrams Develop code samples, integrations, and applications to demonstrate best practices and minimize customer development time, across a variety of languages and frameworks Support customers throughout the presales, proof of concept, and integration processes, assisting with common coding issues and patterns or troubleshooting Creating and maintaining public and internal documentation to help scale the team Act as the internal and external expert in the integration and usage of the CLEAR identity platform Collaborate across Sales, Product and Engineering to ensure that CLEAR strategically incorporates customer feedback and new product features into our roadmap Stay up-to-date with the latest trends and developments in the Healthc