System Power Engineer in New York

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role You will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the Financial Services vertical, partnering with banks, asset managers, and private capital investors to deploy next-generation AI capabilities across their operations, investment processes, and portfolio companies. You will own delivery end-to-end: embedding with Financial Services customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in New York City. We use a hybrid work model of 3 days in the office per w

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

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. Marketing at Brex Marketing tells the story of Brex to the world. From acquisition to activation, we translate product value into business results. Our team spans Revenue, Product, and Brand Marketing, and works closely with nearly every function at Brex. We move fast, experiment often, and think deeply about customer behavior. If you want your creativity to drive growth and shape perception, this is the place. What you’ll do The Brex Marketing team is looking for an experienced Senior Marketing Operations Manager to architect and optimize our B2B sales-led and channel-driven GTM engine. This role will define and maintain the systems, processes, and operational rigor that align Marketing, SDR, Sales, and Partner teams. We are looking for someone who is eager to design the future-state GTM tech stack—modernizing how leads flow, how insights are generated, and how operational workloads become more efficient through automation, AI, and a

VTS's Lease integrations connect our platform to the property management and accounting systems - Yardi, MRI, JDE, and others - that our customers run their portfolios on. When those integrations are healthy, data flows automatically and customers trust what they see in VTS. The Integrations and API Support Advisor owns the health of these integrations end-to-end - proactively monitoring for failures before customers notice them, and resolving the inbound requests that come in when something breaks or needs to change. Success in this role is simple to state and hard to deliver: every integration stays active, and customers can always rely on the integrity of the data VTS is showing them. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** What you can expect as an Integrations and API Support Advisor: At VTS, you'll join the Integrations Support team as a critical layer between our customers' source systems and the VTS platform. You'll: Own Integration Health : Monitor active Yardi, MRI, SAP, and custom API integrations for failures, stalled syncs, and missed feeds. Proactively identify and resolve issues - such as failed nightly imports, integrations stuck in "processing," or ETL files not arriving via SFTP - before they escalate into customer-reported problems. Resolve Data Integrity Issues : Investigate and fix discrepancies between VTS and source systems, including mismatched square footage, missing or duplicated leases, orphaned records, incorrect rent or lease terms, and unit/space mapping errors. Trace root causes across the integration pipeline rather than just patching symptoms. Manage the Customer Support Queue : Respond to and resolve inbound tickets covering the full integration lifecycle - API credential and access requests, asset archiving and disposition processing, source ID/BU remapping, stacking and site plan corrections, and MRI/Yardi version upgrades and migrations. Par

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—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: As organizations rapidly invest in AI applications and build out AI labs, telemetry volumes are growing exponentially and costs are becoming unpredictable. From LLM interactions to agentic workflows, AI systems generate unpredictable streams of logs, driving up costs and making it harder to maintain efficient observability. These challenges are critical for organizations in regulated industries with strict data residency requirements, where data must remain within controlled environments. Datadog’s Bring Your Own Cloud (BYOC) team is reimagining what observability and security look like at petabyte scale in the AI era. The Opportunity: The Group Product Manager - Bring Your Own Cloud (BYOC) role is responsible for defining and bringing to market the next generation of telemetry analytics and insights capabilities in an AI-first environment. This role is highly technical and creative in nature as you will envision novel ways to enable customers to cost-effectively explore, analyze and report over petabytes of data through a welcoming and easy-to-use interface. You will partner with various teams to take advantage of BitsAI capabilities and surface critical insights on volume usage and retention for popular use cases. 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 and grow a team

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. 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 help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

As the Senior Product Manager for the Actions & Automations team, you will own the ecosystem that enables customers, partners, and Datadog teams to build, deploy, and operate AI agents on Datadog. You will drive the strategy and execution for the platform capabilities, developer experience, integrations, and extensibility model that make Datadog the best place to build agents that understand and act on production systems. Modern engineering organizations are entering a new era where software is not only monitored and operated by humans, but increasingly by AI-powered agents. As agentic workflows reshape how teams build, operate, secure, and troubleshoot systems, customers need a platform for creating specialized agents, connecting them to business and engineering systems, governing their behavior, and extending them to solve unique organizational problems. You will define and build the ecosystem that makes this possible. Agent Builder sits at the intersection of Datadog's products, AI capabilities, and ecosystem strategy. You will have the opportunity to work across the breadth of the Datadog platform, partner with teams throughout the company, and help establish Datadog as the foundation for operational AI. 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: Define the vision, strategy, and roadmap for Datadog's Agent Builder platform and ecosystem. Own the core platform capabilities that enable customers and partners to create, customize, deploy, and manage AI agents. Drive the extensibility model for agents, including integrations, tools, actions, context sources, APIs, SDKs, and developer workflows. Shape how agents perform actions across Datadog products and third-party systems. Partner closely with AI, platform, infrastructure, and product tea

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

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 OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, e

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As the Product Manager for Tax, you will own the vision, strategy, and roadmap for Ramp’s next generation of AI-powered tax products. You will build solutions to automate tax calculation, validation, and filing for our existing suite of products (card, bill pay, banking, etc), for both domestic and international use cases. You’ll also be accountable for **expanding** Stack - our agentic accounting product - into the tax automation domain, to automate the work of CPAs. You’ll partner closely with engineering, design, data, and cross-functional stakeholders (Finance, Legal, Security, CX, Sales) to build intelligent experiences that help customers save money, reduce risk, and eliminate manual work. This role blends AI-native product development (LLM-powered workflows, evaluation systems, human-in-the-loop design) and deep domain expertise in domestic/international tax and CPA’s workflows. You will define and execute a strategy that will unlock new markets for Ramp and help us save our customers even more time and money. Please note that

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 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 Senior Staff Engineers are technical leaders operating at the forefront of large-scale systems design, building the infrastructure that will support our next five years of growth and beyond. They do this in three major ways: As individual contributors, they bring world-class technical depth to build industry-leading systems in areas such as observability data platforms, distributed query engines, and real-time event streaming at global scale. As technical leaders, they apply broad architectural perspective and deep systems thinking to align design decisions across teams and domains. They work across complex, multi-team problem spaces to define long-term technical direction, drive large-scale initiatives forward, and ensure consistent execution. As engineering stewards, they play a key role in evolving our systems and engineering culture. They actively participate in Datadog’s senior technical community, bringing external insights and internal experience to elevate engineering standards and mentor the next generation of technical leaders. Examples of projects a Senior Staff Engineer may lead include designing and launching a new distributed data storage engine capable of handling hundreds of millions of records per second, building the real-time infrastructure behind a new observability product, or re-architecting a core service to support exponential growth in throughput and complexity. What You’ll Do: Be the technical owner of multiple critical systems or architecture areas, often spanning several t