Strategic Operations Lead in New York

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Manager, Applied Field Engineering - AI/ML Product Specialists to lead a high-performing team of Applied Field Engineers within the Applied Field Engineering organization. In this hands-on leadership role, you will manage a team of Applied Field Engineers who specialize in Generative AI, Machine Learning, and Advanced Analytics. You will be responsible for coaching your team through technical sales engagements, driving execution excellence, and ensuring customers successfully activate and consume Snowflake's AI/ML capabilities. You will translate team-level insights into feedback that shapes broader strategy, working closely with your manager and cross-functional partners to align execution with organizational priorities. Responsibilities & Focus Areas: Technical Execution & Consumption Activation: Drive team performance toward Consumption Activation — ensuring customers successfully move workloads into production and realize contracted credit value Coa

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

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? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics & Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line. As a Data Engineer, you will: Work directly on new customer experiences built on one of the most advanced AI systems in the world Collaborate daily with researchers and engineers who are some of the best in the world at what they do Run implementations end-to-end and see initiatives through to real outcomes Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy You may be a good fit if you have: 5+ years of experience working on production-grade data processing systems Strong command of Python and SQL Experience with distributed data processing frameworks such as Apache Beam, Spark, or

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. The FinOps function is responsible for financial accountability, visibility, and optimization across all engineering-related spend at Plaid. This includes cloud infrastructure, AI/ML and data workloads, third-party SaaS tools, and other technical investments that support Plaid’s products and internal platforms. The team operates at the intersection of Engineering, Product, and Finance, ensuring that spending decisions are transparent, intentional, and aligned with product strategy and business priorities. Rather than functioning as a cost-control or approval layer, FinOps enables teams to understand, own, and optimize their spend while maintaining engineering velocity. Responsibilities Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities. Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks. Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans. Leads cost optimization initiatives, such as rightsizing, commitment strategies, an

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. The design team at Plaid is made up of product designers, researchers, and content strategists who work with our cross-functional partners to create Plaid’s products. Please visit https://designedbyplaid.com/ to learn more about the Design team. As a Product Design Manager on the Dashboard team, you will manage a multidisciplinary team of product designers and a researcher, leading design efforts across multiple product areas at Plaid. As a member of each area’s cross-functional leadership team, you will partner closely with product and engineering to shape direction and outcomes. Your day-to-day responsibilities will include coaching individual contributors, driving high-quality design execution, and collaborating with PM leads to develop product strategy. Alongside owning near-term delivery, you and your team will also define and advance the long-term vision for how Plaid’s products evolve. On the Dashboard team, we focus on shipping experiences and elevating the UX quality of Plaid’s Dashboard— a key surface area for customers and data partners. The Dashboard provides a variety of features and tools for launching with Plaid, integration monitoring, and account management and is the home of emergi

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity Postman is hiring a Manager of Account Development, a critical role in building and scaling our presence in the US. As a Manager of Account Development, you’ll recruit, coach, and lead a team of Account Development Representatives (ADRs) focused on uncovering new business opportunities and creating a strong pipeline for our Corporate Sales team. You’ll collaborate with Sales, Marketing, and other cross-functional teams to drive our go-to-market strategy and establish a culture of sales excellence in the United States. What You'll Do Build and lead a world-class team: Recruit, train, and develop a high-performing team of Account Development Representatives in the United States. Implement AI workflows and drive productivity improvements with an excellent suite of AI technologies. Provide hands-on coaching: Teach foundational sales skills, including account research, prospecting, cold calling, and high-level discovery. Drive data-informed decisions: Leverage analytics and performance metrics to align the team’s strategy with our broader go-to-market goals. Foster sales excellence: Model and reinforce Postman’s values,

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. 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: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people. You'll sit at the center of Datadog's biggest talent bets for Engineering: how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles. You’ll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale. AI is changing how Engineering builds software, and it is changing how People builds the programs that support Engineering too. This role sits at the centre of both: understanding how AI is reshaping engineering roles, skills and structures, and building AI-powered solutions within People to keep pace. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles. Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures. Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices. Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role. Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes. Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business. Operate in ambigu

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

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

Developers are shipping more code than ever, accelerated by AI-assisted development and increasingly complex software delivery workflows. As a Product Manager II on the Developer Engagement team, you'll help bring Datadog's insights and automation directly into the tools developers use every day, making software delivery faster, safer, and more efficient. You'll define customer-facing experiences that connect Datadog's observability, CI/CD, testing, security, and AI capabilities with pull requests, code reviews, and developer workflows. This role offers the opportunity to work closely with customers, engineering, design, and go-to-market teams while shaping the future of software delivery for developers. 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: Partner with customers, developers, platform engineering teams, and internal stakeholders to understand software delivery challenges and identify opportunities to improve developer workflows. Own the product strategy and roadmap for developer-facing experiences within pull requests, code reviews, and source code management platforms. Collaborate across Software Delivery products to surface actionable insights from CI/CD Optimization, Test Optimization, Code Coverage, Code Security, Deployment Gates, Bits AI, and future capabilities. Work across source code ecosystems including GitHub, GitLab, Azure DevOps, Bitbucket, and enterprise environments to deliver scalable integrations. Partner with engineering teams to connect Datadog signals with recommendations, AI-assisted workflows, generated fixes, and future automated remediation experiences. Measure product success using customer adoption, engagement, feedback, and business outcomes while partnering with Sales, Product Marketing, Solutions Engineering, Custo

As the Senior Product Manager for Network Path, you’ll own the vision, roadmap, and execution for how our customers visualize, monitor, and troubleshoot network traffic across complex hybrid and cloud environments. You’ll work closely with a diverse set of Network, DevOps, and SRE teams to understand how they manage their infrastructure, what challenges they face regarding network visibility and routing, and how our product can help them better observe, isolate, and remediate latency, packet loss, and connectivity issues across the public internet, cloud providers, and private data centers. In addition, you’ll work with product teams across the organization to identify opportunities to create integrated experiences—bridging the gap between infrastructure monitoring, application performance, and network health—and you’ll partner with engineers, designers, and go-to-market teams to drive adoption across thousands of customers. 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 strategy and pioneer new ways to visualize end-to-end network paths. You will determine how we capture, analyze, and map complex routing data to give customers a true hop-by-hop view of their network traffic. Own the core Network Path roadmap, ensuring deep coverage for cloud-native networking (e.g., AWS VPCs, Transit Gateways), SD-WAN, and traditional on-premise routing topologies. Explore ways to combine flow and metrics to provide a holistic view of network health and pinpoint the problem. Partner with Product Marketing to articulate the business value of network path monitoring, showing customers how improved visibility directly correlates to reduced MTTR and optimized cloud egress costs. Identify opportunities to build intelligent alerting and root-cause analysis c

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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 strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. This role is based in San Francisco, CA. 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 identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be based in San Francisco or New York City. 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: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

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 You'll own the quality bar for Notion AI products. You’ll work with product and engineering teams to build systems to define what “good” looks like, measure our progress, and drive changes to deliver reliable and high-quality AI experiences. Your work directly shapes how Notion's AI products behave for millions of users. This isn't a traditional software engineering role. It’s an art & science role . You won't spend your days writing code. Instead, you'll focus on understanding and shaping how our AI products behave through context engineering, designing evaluation systems, and analyzing data. This team sits in our AI engineering team, working directly with engineering, product, design, and data. This role is a unique blend of ops, strategy, and product thinking. Day to day, you'll live in production data, ship prompt fixes, run evals and, in effect, shape our quality strategy. As part of that you'll shape Notion's model strategy and work directly with frontier AI labs (OpenAI, Anthropic, Google) to evaluate and launch new models. We're looking for problem-seeking generalists interested in 0 → 1 : curious people wi