Operations Business Partner Director in New York

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

VP, Product Insurance underwriting runs on human judgment, manual workflows, and knowledge locked in someone's head. It breaks when that person leaves and doesn't scale when the book doubles. Sixfold is building AI agents that understand risk the way a 20-year veteran underwriter does. Not summaries or flags, but systems that make real decisions on billions in premium for some of the world's largest carriers. AI is the product, the workflow, and the moat. If you think in systems, move fluidly from research to pixels, and are energized by designing AI-native experiences where the best practices haven't been written yet — this role was made for you. Who We Are 🏔 Product: Sixfold is the AI brain for underwriting. Our platform handles submissions at scale, assessing risk against appetite, surfacing cited insights, and deploying AI agents to handle research, referrals, and triage so underwriters can focus on building profitable portfolios. 💪 Team: A focused team of insurance operators, AI researchers, and engineers who love hard problems. We've pushed the boundaries of what AI can do with unstructured data — from teaching AI to understand that a bakery in Florida faces different risks than one in Montana, to knowing when a manufacturing company's pivot from toys to medical devices fundamentally changes their risk profile. We ship fast and stay close to customers. 📈 Traction: Processing billions in premium for some of the world's largest carriers. We know AI. We know underwriting. We're building what comes next. About the Role You'll inherit a strong product and a capable team, but that's the starting point, not the job. The job is figuring out what underwriting becomes once AI stops assisting and starts deciding, and getting there faster than the market expects. You prototype to find out, not to perform speed. You're drawn to this problem because the underwriter of the future is one of the more interesting design problems in software right now. In this role, you will:

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The tvScientific by Pinterest team is building a new enterprise cross-sell motion focused on growing off-platform revenue in close partnership with Pinterest’s NAMER Enterprise sales team. As a Senior Client Partner, you’ll help establish how we go to market together across CTV, video and programmatic opportunities, creating a seamless experience for customers with integrated needs. You’ll play a key role in shaping the team’s operating model, strengthening collaboration across sales teams and driving incremental revenue across enterprise accounts. What you’ll do: Lead enterprise cross-sell efforts for tvScientific by Pinterest in partnership with Pinterest’s NAMER Enterprise sales team, with a focus on growing off-platform revenue across CTV, video and programmatic opportunities Build and execute joint account plans with Enterprise Client

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

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 and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

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 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).

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

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. Our Fraud Intelligence team's mission is to turn fraud signals into insight that our EPD teams transform into improvements across Protect, IDV, Signal, and Guaranteed Payments. We believe transaction patterns, device signals, identity linkages, and behavioral data are dramatically underleveraged tools in fraud prevention, and we ground our products in what adversaries are actually doing right now. As the Fraud Intelligence Lead, you will build and run a small, high-leverage team of Fraud Intelligence Analysts (and eventually a Staff Researcher) responsible for live casework across Protect, IDV, and Payments/ACH. You'll operate as a player-coach, hiring and coaching your team while staying close enough to the work to personally pick up casework and SEV response when needed. Responsibilities Team Building & People Leadership Set the casework quality bar: define what rigorous investigation, triage, and reporting look like for the team Coach analysts on investigation technique, pattern synthesis, and translating findings into product/model input Operating Model & Cross-PA Partnership Own coverage allocation across the Protect/IDV and Payments/ACH pods, including flexing assignments as volume shi

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

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.

We're looking for an Engineering Manager II to own and grow the Observability Pipelines engineering org at a pivotal moment in the product's lifecycle. Observability Pipelines is Datadog's on-premise, vendor-agnostic telemetry pipeline product, with a lot still to build as it grows and scales. It sits at the center of a fast-consolidating market, is central to Datadog's data pipeline optimization story for Logs and Metrics customers. This is a build-and-scale opportunity: you'll grow the management and technical leadership layers, co-own the roadmap with Product, and define how this org operates as it continues to expand. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Directly manage the OP org including EM1s across NYC and Paris, set technical direction, and be the connective tissue across a distributed team Build out the management and technical leadership layers as the org continues to grow - today ~20 ICs Partner directly with Product to co-own the roadmap and strategy, helping decide where OP’s engineering investment goes next Set and evolve the operating rhythm across the group: planning cadence, on-call and incident standards, and cross-team alignment Own key cross-org relationships with the SaaS Logs Pipelines team, the BYOC team, and the Vector open-source community Coach managers and senior engineers, and build the succession and growth plans that let the org scale beyond you Who You Are: Experienced managing managers across distributed teams, with a track record of raising the bar on how those teams operate, not just delivering through them Back

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 Senior Manager, Customer Success Engineering to help lead Customer Success Engineering in North America. This leader will manage CSEs, ensuring the team is focused on the customers where Postman can create outsized impact, while providing the coaching, inspection, and operational discipline required for consistently high-quality execution. This is a highly cross-functional leadership role and a critical partner to Sales. The leader will work closely with North America Sales leadership, with a strong focus on East Coast alignment, to prioritize accounts, shape technical engagement strategy, allocate CSE capacity, and ensure customer execution is progressing with urgency and discipline. CSEs help customers embed Postman into real engineering workflows across API design, governance, CI/CD, developer platforms, integrations, modernization, migration, automation, quality enforcement, and service discoverability. This is not about general support or enablement; CSEs are laser-focused on turning Postman from a beloved developer tool into critical API infrastructure. The right leader is an experienced po

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. What You’ll Do Regional & Executive Leadership Own the overall Americas Channel Sales strategy, operating model, and results across Enterprise West, Enterprise East, LATAM, and Federal/SLED. Build, lead, and scale the Americas channel team hiring, developing, and retaining 4-5 regional channel ICs plus evolving Americas-wide scope. Establish clear priorities, coverage models, KPIs, and operating rhythms aligned to global Postman objectives. Act as the senior leader and voice for Americas Channel within Postman. Partner Ecosystem Strategy Define and execute the Americas partner strategy across SIs, resellers, distributors, and technology alliances. Build a scalable, services-capable partner ecosystem (WWT, SHI, CDW, Insight, SoftwareONE, Carahsoft, plus FSIs BAH, Deloitte Federal, Accenture Federal Services, Leidos, SAIC, CGI Federal, GDIT, CACI plus LATAM partners including Caylent, Mission Cloud, and regional SIs). Ensure partners are enabled, certified, and accountable for sourcing, selling, and delivering Postman Enterprise. Revenue & Pipeline Ownership Own partner-sourced and partner-influenced pipeline and revenue acro