Operational Risk And Controls Senior Jobs

MongoDB Atlas is the premier multi-cloud database-as-a-service built and operated by the makers of MongoDB. The Cloud Operations Engineering team at MongoDB is a worldwide team responsible for the consistent operational success of every MongoDB Atlas customer. As a Cloud Operations Engineer, you will help ensure the success of our Atlas customers, whether they are early startups or large multinational companies, cloud-native or just getting started with a digital transformation to the cloud. You are excited about the core mission of MongoDB, and the opportunity to join the team responsible for operating Atlas, the fastest-growing multi-cloud database-as-a-service in the world. You are prepared to be one of the early members of a 24/7/365 global cloud operations team. Cloud Operations Engineers will be responsible for day-to-day duties such as creating and monitoring system’s alert dashboards, reviewing critical events and system logs, accessing customer instances that underpin their production databases and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. At MongoDB you will grow your career and skills, wear multiple hats, and be part of an operations team that works at the frontier of Cloud services and database systems. We are looking to speak to candidates who are interested in working out of our Dublin or Cork office under our in-office working model Monday to Friday. Due to the 24/7 nature of our support organization, certain events throughout the year will require volunteering for coverage outside one’s normal work days or work hours (i.e. regional offsites, regional holidays, etc). These are typically announced weeks in advance with a sign-up system that considers equitability. Responsibilities Successfully coordinate and collaborate with a global team of Cloud Operations Engineers wh

MongoDB Atlas is the premier multi-cloud database-as-a-service built and operated by the makers of MongoDB. The Cloud Operations Engineering team at MongoDB is a worldwide team responsible for the consistent operational success of every MongoDB Atlas customer. As a Cloud Operations Engineer, you will help ensure the success of our Atlas customers, whether they are early startups or large multinational companies, cloud-native or just getting started with a digital transformation to the cloud. You are excited about the core mission of MongoDB, and the opportunity to join the team responsible for operating Atlas, the fastest-growing multi-cloud database-as-a-service in the world. You are prepared to be one of the early members of a 24/7/365 global cloud operations team. Cloud Operations Engineers will be responsible for day-to-day duties such as creating and monitoring system’s alert dashboards, reviewing critical events and system logs, accessing customer instances that underpin their production databases and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. At MongoDB you will grow your career and skills, wear multiple hats, and be part of an operations team that works at the frontier of Cloud services and database systems. We are looking to speak to candidates who are interested in working out of our Dublin or Cork office under our in-office working model Monday to Friday. Due to the 24/7 nature of our support organization, certain events throughout the year will require volunteering for coverage outside one’s normal work days or work hours (i.e. regional offsites, regional holidays, etc). These are typically announced weeks in advance with a sign-up system that considers equitability. Responsibilities Successfully coordinate and collaborate with a global team of Cloud Operations Engineers wh

MongoDB Atlas is the premier multi-cloud database-as-a-service built and operated by the makers of MongoDB. The Cloud Operations Engineering team at MongoDB is a worldwide team responsible for the consistent operational success of every MongoDB Atlas customer. As a Cloud Operations Engineer, you will help ensure the success of our Atlas customers, whether they are early startups or large multinational companies, cloud-native or just getting started with a digital transformation to the cloud. You are excited about the core mission of MongoDB, and the opportunity to join the team responsible for operating Atlas, the fastest-growing multi-cloud database-as-a-service in the world. You are prepared to be one of the early members of a 24/7/365 global cloud operations team. Cloud Operations Engineers will be responsible for day-to-day duties such as creating and monitoring system’s alert dashboards, reviewing critical events and system logs, accessing customer instances that underpin their production databases and performing server administration duties including performance troubleshooting. Applicants must be critical thinkers who are quick to detect, resolve, or escalate issues that are sometimes broad in scope and difficult to trace. At MongoDB you will grow your career and skills, wear multiple hats, and be part of an operations team that works at the frontier of Cloud services and database systems. We are looking to speak to candidates who will be based remotely in Ireland. Due to the 24/7 nature of our support organization, certain events throughout the year will require volunteering for coverage outside one’s normal work days or work hours (i.e. regional offsites, regional holidays, etc). These are typically announced weeks in advance with a sign-up system that considers equitability. Responsibilities Successfully coordinate and collaborate with a global team of Cloud Operations Engineers who are tasked with ensuring our uptime guarantees to our Atlas customer base

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft's Airport Partnerships team manages the company's relationships with airport authorities across the U.S. and Canada, ensuring Lyft operates as a trusted, compliant, and collaborative partner at every airport we serve. The team is organized by region, with each Business Development Manager owning the airport relationships within their territory. This role owns the Northeast region, covering U.S. states from the Northeast through the Mid-Atlantic and Carolinas, and Canadian provinces from Ontario and Quebec eastward. As a qualified candidate, you're comfortable operating across a wide range of altitude — from negotiating agreements with senior airport officials to processing day-to-day operational requests like driver suspensions and fee changes. You know how to build and adapt relationships with airport partners, whose working styles range from informal and high-touch to highly formal and bureaucratic, and you're equally skilled at translating airport needs into requirements that Lyft's internal teams — legal, compliance, product, finance, and marketing — can act on, and vice versa. You are self-directed and highly organized, able to manage a mix of reactive, ad hoc requests and longer-term strategic projects without close oversight, and you take pride in being a collaborative business partner to airports while knowing when to push back. Responsibilities: Own airport relationships across the Northeast region by serving as Lyft's primary point of contact for airport authorities across the region's states and provinces, adapting your communication style and cadence to each partner's preferences Deliver on airport requirements by coordinating cross-functionally with legal, compliance, product, finance, reporting, and marketing teams, translating airport mandates into internal action and Lyft's capab

Role Description You will act as the primary regional business partner for sales executives, supporting sales planning, territory and quota execution, forecast interpretation, operational improvements, and translation of strategic priorities into clear execution plans. You’ll drive process clarity, pipeline health, forecasting hygiene, and cross-functional governance, using AI and automation-enabled workflows to reduce manual reporting effort while maintaining strong human judgment over business recommendations. Drive operational excellence in account segmentation, territory planning, quota planning and execution, building the frameworks and analyses that guide how we assign and manage books of business . Act as the strategic business partner to Sales leadership, helping shape regional go-to-market strategy and execution across two distinct sales organizations. Drive operational excellence by improving forecasting, pipeline health, sales planning, and execution while balancing the unique commercial priorities, growth opportunities, and operating models of each region. As a member of the APJ Leadership Team, help define and execute the regional GTM strategy, driving operational excellence and sustainable growth across the APJ region. Drive forecasting accuracy, pipeline health, and business performance through executive-ready insights, standardized operating rhythms, and continuous improvement of data quality and reporting. Own and continuously improve the Run-the-Business (RTB) operating cadence - including forecast reviews, pipeline inspections, business reviews, and executive reporting - to improve operational rigor and decision-making. Lead cross-functional initiatives with teams, including Sales, Marketing, Operations, Finance, Legal, HR and Product to drive alignment and support decision-making. Communicate complex business insights and recommendations to executive stakeholders through concise, data-driven presentations and business reviews. Responsibilities Ow

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Go-to-Market (GTM) Planning Strategy and Operations team works at the intersection of corporate planning, GTM Strategy, Product, GTM and Regional Strategy and Operations with responsibility for ensuring that we land the Stripe annual rhythm in a smooth and timely manner. This entails three main pillars: • Building and landing foundations (tooling, process, and strategic changes) for next cycle • Ensuring budgets, territories, targets, comp plans, reporting, and enablement are delivered to GTM in a timely manner • Effectively managing in-year Account, Territory, Quota, and Adjustments Within this organization, the Central Policy and Operations team owns the processes, systems, and automation that power territory management, account placement, segmentation, and business adjustments at scale—processing over 10,000 account movements per month and operating critical workflows that serve the entire GTM organization at scale. What you’ll do We're seeking an experienced systems practitioner to own the end-to-end processes, Mechanization and Automation pillar for Central Operations end-to-end. In this role, you'll be the person who wakes up every day focused on ensuring our support tooling has a clear roadmap, our processes are documented and AI-enabled, and our operational systems are built to scale without adding headcount. You'll take ownership of how we design, build, and evolve the systems that underpin Stripe's territory, segmentation,

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurable

About the Team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the Role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and mea

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're looking for an Optical Interconnect System Engineer to design, qualify, and deploy scalable optical connectivity for large-scale AI infrastructure. This role spans fiber-system architecture, optical-mechanical integration, validation, reliability, deployment, and serviceability. You will work with optical, mechanical, electrical, networking, manufacturing, reliability, and data-center teams to translate system needs into practical interconnect solutions. This is a hands-on role for someone who can connect design decisions with installation, qualification, troubleshooting, and long-term operational performance. In this role, you will: Define optical interconnect architectures and requirements across hardware platforms and rack-level systems. Design high-density fiber systems for performance, density, reliability, installation, and serviceability. Lead optical-mechanical integration and cross-functional design reviews. Develop test and qualification plans for optical components, modules, switching platforms, and integrated systems. Own optical loss budgets, routing guidelines, handling requirements, and serviceability criteria. Support system bring-up, deployment, troubleshooting, failure analysis, and reliability improvement. Create reusable design guidelines, interface requirements, and qualification methods. You might thrive in this role if you have: Core experience Experience desi

About the Team GTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness. We apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight. Our work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams. About the Role We're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs. This is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact. You will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity. In this role, you will: Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes. Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context. Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows. Investigate why a

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. Our team builds the software, tooling, and operational systems that help manage this fleet at scale. We work across production engineering, distributed systems, capacity management, and operational automation to improve reliability, reduce manual work, and make better use of available compute. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will develop the systems that help manage the GPU fleet powering ChatGPT, including tooling for fleet health, capacity planning, operational automation, and incident response. You will work closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and compute utilization. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build software and internal tools to manage large-scale GPU infrastructure supporting ChatGPT inference. Develop systems for capacity planning, fleet health monitoring, and resource utilization. Automate operational workflows, including incident detection, diagnosis, and response. Identify and address bottlenecks affecting fleet reliability, scalability, and performance. Partner with infrastructure, research, and product engineering teams to improve the compute platform. You Might Thrive in This Role If You Have experience operating large-scale production infrastructure, GPU clusters, or other compute-intensive distributed systems. Have a background in production engineering, site reliability engineering, infrastructure engineering, or platform engineering. Have built software that automates operational workflows and reduces manual work. Have worked with distributed infrastructure, cluster orchestration, or large-scale int

About the Team The Treasury team is responsible for protecting liquidity, enabling scale, maintaining strong controls, and helping the company operate with clarity and resilience. We work across finance and operational partners to ensure funds move safely, visibility remains high, and Treasury infrastructure keeps pace with a fast-moving business. As hands-on operators and builders, we combine financial judgment with AI, automation, and data to solve problems faster, strengthen controls, and continuously improve how Treasury operates. About the Role We’re looking for a Treasury Manager to own and execute critical activities across OpenAI’s global treasury operations, including cash management, payments, bank account management, forecasting support, controls, and reporting. Beyond day-to-day operations, this person will support Treasury leadership on high-impact projects such as M&A integrations, new legal entity formation, and geographic and currency expansion. They’ll also help build scalable, AI-enabled systems, workflows, and controls for a rapidly growing global business. This is an individual contributor role with broad scope, spanning operational ownership and building an AI-native Treasury function. This role is based in our San Francisco HQ. 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: Own core global treasury operations across cash positioning, payments, bank account management, portal administration, forecasting support, and FBAR preparation. Coordinate day-to-day execution for intercompany funding, settlements, investment operations, letters of credit, guarantees, treasury close, and related accounting handoffs. Automate and scale treasury workflows for request intake, approvals, payment tracking, bank account changes, KYC follow-up, access reviews, evidence collection, and issue resolution. Identify recurring processes, manual pain points, duplicate work, control

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A