It Operations Engineer in New York

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. Finance at Brex The Finance team is a strategic engine at Brex. We lead planning, forecasting, capital allocation, and ROI analysis — partnering across the business to drive clarity and unlock opportunity. We partner across teams at Brex to ensure our business is building and planning with the same dream big goals throughout our entire organization. We’re not here to report on outcomes; we shape them. If you want to influence company direction and think long-term about value creation, this is where your ownership starts. Cross-functional alignment: We work on complex problems that cut across Engineering, Product, Design, Sales, Marketing, Revenue Operations, CX, and more. This requires the ability to generate buy-in from a wide set of stakeholders on key initiatives. Business intelligence: We are a data-driven organization that always provides data to support our decision-making. When data is not available, we find it in market

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

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization. Lyft connects people to transportation to change the way we live and get around our communities. We are looking for product leaders who bring exceptional creative and analytical skills to drive forward a best in class product. Product management at Lyft leads the integration of engineering, data science, and design to achieve the company’s vision for reinventing transportation. We are looking for entrepreneurial and passionate product leaders to innovate and execute across a rapidly growing, fast paced company and industry from our San Francisco and New York offices. The Safety & Customer Care (SCC) Product team builds the platforms, products, and experiences that support riders and drivers when they need help most — and help keep them safe every time they ride. As the Director of Product, Customer Care, you’ll lead a team of product managers driving Lyft’s customer care strategy end to end: AI-powered support across chat and voice, the contact center platforms our support teams run on, and the underlying data layer which is critical to understand where our products can be improved. It’s a rare chance to shape how a category-defining company delivers support at scale — across emerging AI capabilities, global expansion, autonomous vehicle partnerships, and new lines of business. Responsibilities: Own the vision, strategy, and multi-year roadmap for Lyft’s Customer Care product portfolio — spanning AI-driven support automation, contact center platforms, self-service and issue resolution, and the trust and safety products underpinning every interaction Lead, coach, and grow a team of product managers, setting a high bar for product craft, execution, and career development Partner with senior leaders across engineering, data science, design, operations, and finance to set priorit

Role Summary: Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines with log management software that customers deploy and manage in their own infrastructure. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at scale. 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: Make customer-controlled deployments feel like a managed Datadog product: deployment, upgrades, configuration, observability, diagnostics, reliability, and secure operation across diverse customer cloud environments Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably that customers deploy and operate within their own cloud infrastructure. Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have significant experience building software that is installed, deployed, and operated in customer environments rather than only as a fully managed SaaS service. You have strong expertise in distributed systems,

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

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

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 Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform. This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness. You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient. What You'll Work On: Detection Engineering Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents Improve visibility across cloud infrastruc

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’re looking for an experienced Machine Learning Engineer to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Machine Learning Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform - one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: Python / Postgres / Snowflake / dbt AWS SageMaker and MLflow What you'll do: Own and drive the foundational work of a ML system at CLEAR Design, build and deploy ML models for various applications, such as document and image processing, fraud detection. Develop and implement robust data pipelines at a variety of scales, including collection, pre-processing, transformation, and feature engineering Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 3+ years of experience building, operating and scaling ML models for consumer applications, particularly those with experience building end-to-end systems Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance Expertise in best practices for feature enginee

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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

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 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: Datadog’s Staff Engineers are our technical leaders operating at the forefront of technology, building solutions that take us through at least our next five years of growth. They do this in three major ways: As individual contributors, they bring world class technical abilities to deliver industry leading systems in areas such as data visualization, virtual runtime profiling, and planet scale streaming. As technical leaders they bring experienced technical breadth and communication skills to tackling design and architectural problems spanning the organization, charting the right course, then leading delivery. In both roles they participate in the staff engineering community and help us learn from what the industry is doing and what we've built before, and so improve company wide standards around software and systems engineering. Some examples of projects a staff engineer may own include designing and building a new data storage engine handling hundreds of millions of records per second, being the lead engineer building a new product like synthetics or profiling, or rebuilding a critical service to handle the next two orders of magnitude of scale. What You'll Do: Be the technical owner of multiple pieces of critical architecture in your area of the business Own delivery of the systems you architect from beginning-to-end, doing what it takes to get things shipped and at full scale in production Dive deep into performance of systems; inventing new approaches that bring efficiency at scale Who You Are: You have a BS/MS/P

About the Team The Astral team builds high-performance developer tools to power the future of programming, at OpenAI and beyond, including Ruff, uv, and ty. The Astral toolchain sees hundreds of millions of installs per month and powers hundreds of millions of package downloads per day for the Python ecosystem. As a team, we are building on those foundations to continue solving impactful tooling problems as programming evolves. About the Role We are looking for an experienced software engineer to build next-generation programming language tooling. If you like writing high-performance Rust, it could be a good fit; if you like thinking about the future of programming, it could also be a good fit. Strong candidates tend to have deep experience with Rust, Python, open source, compilers, or developer tools — but few candidates are deep in all of these areas, and we've hired candidates without prior Rust or Python experience. In this role, you will: Design and implement features in Astral’s existing open source projects (Ruff, uv, ty, and python-build-standalone, and more). Support Astral’s open source projects as a maintainer, triaging user issues, reviewing pull requests, and participating in community discussions. Evolve the Astral toolchain to accelerate development velocity at OpenAI. Build entirely new tools, in entirely different programming ecosystems, to power the future of agentic software development. Your background might look something like: 5+ years of professional engineering experience, excluding internships, in relevant engineering roles. High agency and comfort operating in a fast-moving environment, with strong ownership of security, reliability, and operational excellence. Strong developer empathy and communication skills, including experience maintaining open source projects. Exceptional systems engineering fundamentals and a track record of leading complex projects from ambiguous problem statements through to user impact. Proficiency in one or more s

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid's Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget

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 collaborative, strategic, and execution-focused engineering leader to shape the digital experiences that millions of people have with CLEAR. As a Director of Engineering, you will lead multiple engineering teams responsible for building and scaling our consumer products across the CLEAR mobile app, website, digital enrollment experiences, marketing technology, and Concierge platform. You'll partner closely with Product, Design, Marketing, and business leaders to create intuitive, high-performing experiences that drive acquisition, engagement, conversion, and member satisfaction. The ideal candidate combines strong technical leadership with a deep understanding of consumer product development, building high-performing teams that move quickly while maintaining quality, reliability, and operational excellence. What You'll Do: Lead and grow multiple engineering teams responsible for CLEAR's consumer experiences across mobile, web, marketing technology, and Concierge products. Define and execute the technical strategy for customer-facing applications, ensuring scalable, reliable, and performant experiences that delight millions of members. Partner closely with Product, Design, Marketing, and Business stakeholders to prioritize roadmaps that improve acquisition, conversion, engagement, retention, and member satisfaction. Drive engineering excellence by establishing best practices around architecture, delivery, quality, observability, and operational performance. Build highly collaborative relationships across Engineering, Pro

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s Product team builds the network that powers open finance. At Supplier Products, we focus on building trusted, transparent experiences for financial institutions operating in Plaid’s ecosystem. Responsibilities: You will lead a team of 6 engineers, ranging from mid-level to Staff, developing them through clear goal setting, coaching, and feedback. You’ll define and drive the long-term strategy for this focus area, in close partnership with technical and product leaders across Plaid. You’ll collaborate with cross-functional partners to identify high-leverage opportunities, shape the roadmap, and dive deep into technical design and execution details to ensure consistent delivery of high-impact business outcomes. You’ll uphold a high bar for technical quality and delivery velocity, leading by example. Qualifications: 8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management. 1+ years of engineering management experience Deep experience designing scalable, reliable architectures that support real-world products at scale. Track record of building and growing high performing engineering teams (either as an engineer or a manager). Our mission

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. 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 and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali