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Enterprise Security Sales Specialist Jobs

5,685 active opportunities · Updated for October 2026

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Explore current enterprise security sales specialist jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineeriIng teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our SF or NYC office. 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: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteri

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OpenAI
📍 Sao Paulo• Full-time
1mo ago

About the Team OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise Applied AI Engineer, you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. In this role, you will: Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes. Work hands-on in code to build pr

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About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware aut

awsrestai
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Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange™️ platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 160+ public exchanges globally and thousands of private exchanges at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Sr. Staff Software Development Engineer-AI Security to join our team. This is a Hybrid (based in San Jose, CA or Bellevue, WA with a 3 days in office requirement) role, reporting to the Director of Software Engineering in the Emerging Tech department. You will be responsible for designing and implementing core infrastructure components and distributed systems, serving as a foundational architect for our AI security solution. This high-impact role focuses on scaling security infrastructure to support hundreds of millions of users, collaborating with stakeholders across the development lifecycle to drive innovation and technical excellence. What you’ll do (Role Expectations) Architect, develop, and optimize a low-latency, high-throughput AI Security plane utilizing Rust, specifically leveraging its async/await model for highly efficient I/O and service-oriented architecture Build resi

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Baseten
📍 San Francisco• Full-time
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. PRODUCT AT BASETEN Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer-obsessed, and moves fast. We're building the product function now, and you'd be one of the people who defines it. You'll work directly with our founders and with some of the best systems and infrastructure engineers in the world, and you'll set the standard for what product looks like here. You earn trust by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. THE ROLE The largest, most demanding Enterprises are starting to run on Baseten and they come with a range of security, compliance, and procurement requirements. Today that readiness is assembled deal-by-deal. You'll own the enterprise-readiness surface end to end and turn it into product: the deployment options customers can choose and buy, compliance posture they can trust, access and security controls their IT teams require, and the billing and spend controls their finance teams expect. What does a complete Baseten Enterprise Product offering look like? RESPONSIBILITIES Drive the Enterprise Readiness customer experience end to end: Partner with GTM and Enterprise Engineering to make "enterprise-ready" a platform-wide capability, not a deal-by-deal scramble. Outcome: readiness becomes a supported, priced product instead of bespoke work asse

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Replit
📍 Foster City• Full-time
1mo ago

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're looking for a Product Engineer to join as an early member of our new Enterprise team. The consumer story has demonstrated Replit’s magic and now we are seeing use cases emerge in the B2B space that are ripe for innovation and growth. It is a critical area for our success this year and beyond. You can be part of the journey to build and scale features that help teams and organizations of any size be more productive with Replit. This is an opportunity to make meaningful impact and shape the culture and processes from the ground up. Working closely with cross-functional teams including product managers, designers, and AI engineers, you'll craft solutions that enable our customers to build, deploy, and share their applications seamlessly. This role requires both technical expertise and a deep understanding of user needs to deliver features that make an impact. In this role you will: Build and own features across the full stack that serve enterprise customers, from backend services to user-facing interfaces Design and implement scalable solutions for teams and organizations. This includes enterprise-readiness features like authentication, permissions, security, and compliance, as well as tools that improve team collaboration and drive adoption within an organization. Work directly with customers to understand their needs and iterate on solutions Contribute to technical decisions and architecture for the Enterprise platform Collaborate closely with Product, Design, and other Engineering teams to deliver high-quality experiences Mentor other engineers and raise the bar for engineering excellence Ship quickly and iterate based on customer feedback and usage data Required skills and experience: Strong full

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Coinbase
📍 Brazil• Full-time• Remote
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Software Engineer on the CX Shared Agent Platforms and SFDC Solutions team, you'll build and extend the platforms that power customer service and compliance operations across Coinbase. This team, part of the Enterprise Applications and Architecture org, owns CX tooling including Salesforce, Maestro QA, and Assembled, enabling agents to resolve customer issues and manage KYC workflows with speed and accuracy. You'll develop full-stack services and integrations that drive agent productivity, support strategic platform transitions, and deliver impact at scale from Brazil. What you'll do: Build and ship backend services using Golang and gRPC that extend CX platform capabilities and support agent workflows across compliance and consumer teams. Own the evaluation, integration, and ongoing support of third-party SaaS platforms, ensuring seamless connectivity across the CX tooling ecosystem. Partner with product, design, security, and data teams to deliver cross-functional solutions to complex operational and compliance challenges. Drive engineering best practices across the team, including code reviews, testing strategies, deployment processes, and observability standards (metrics, logging, tracing). Translate complex technical concepts into clear recommendations for non-technical stakeholders across CX, product, and leadership teams. Required Skills and Experience: 5+

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1mo ago

About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI. If you're passionate about doing significant and unique work as a technology lawyer, this team is for you. The team comprises professionals from diverse fields, including technology, AI, privacy, IP, corporate, employment, tax law, regulatory, and litigation. About the Role As a member of our AI Product Counsel team, you will advise the teams building and deploying OpenAI’s business products, including ChatGPT Business, ChatGPT Enterprise, and our API platform. You will partner closely with Product, Engineering, Safety, Security, Privacy, Strategy, Go-to-Market, and other Legal teams on issues spanning enterprise product development, model launches, customer data protections, administrative controls, strategic partnerships, and the responsible deployment of increasingly capable AI models. This is a unique opportunity to help shape how frontier AI products are built and delivered to businesses. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Serve as a strategic legal partner to teams developing ChatGPT’s business products, enterprise features, and API offerings. Advise on product design and launches involving enterprise administration, data governance, identity and access, connectors and integrations, agentic capabilities, and voice and multimodal experiences in the B2B space. Counsel teams on deploying frontier AI capabilities responsibly while balancing customer commitments, safety, security, and privacy. Support strategic partnerships and distribution arrangements, including cloud platforms, resellers, and other third-party channels through which customers access OpenAI models. Partner with Commercial Legal, Privacy, Security, Safety, Product and Product Policy, and Go-to-Market teams on custom

awsrestai
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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI's mission is to ensure that AGI benefits all of humanity. The Business Systems team helps make that mission possible by building the internal products and platforms that allow OpenAI to operate with speed, reliability, and care. We build internal applications and workflows for Finance and Supply Chain. Our work spans product discovery, React and TypeScript interfaces, Python services and APIs, data models, workflow orchestration, enterprise integrations, and the systems that connect people to systems of record. We work directly with the people who use these products and care about correctness, permissions, auditability, and production reliability. Examples of our work include building an integration platform for supply chain integrations, integrations with Oracle Fusion and Zip, contract intelligence applied to B2B revenue recognition, and Temporal-based agentic workflows for credit checks, duplicate bank detection, and invoice triaging. We turn these efforts into reusable patterns that can support many workflows, rather than one-off automations. About the Role We are looking for Product Engineers to build internal applications end to end. This role spans product discovery, user experience, frontend, backend services, data models, workflow orchestration, and integrations with order management, fulfillment, and supply chain systems. You will take a problem from a first conversation with a Finance or Supply Chain partner through design, implementation, rollout, and production support. Strong candidates combine product judgment with engineering depth. You should be comfortable moving between a React interface, a Python API, a durable workflow, and an integration with an enterprise system. You should be able to ship a useful first version quickly while building the foundations for reuse, security, and long-term maintainability. Direct AI experience is helpful, but the core requirement is strong product engineering judgment and reliable execution. I

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Ema (Enterprise Machine Assistant)
📍 San Francisco Bay Area• Full-time• $135K – $225K/yr
1mo ago

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are We are seeking an experienced DevOps Engineer to join our growing team and play a pivotal role in designing and building our platform and infrastructure as we continue to scale our product and user base. As a part of our team, you will be working in a dynamic, fast-paced environment to ensure the reliability, scalability, and performance of our systems, while focusing on service architecture and deployment, query optimization, distributed systems, data and machine learning infrastructure, and security and authentication. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact. You will: Partner with product teams to architect, design, and build the foundational infrastructure for our products. Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on any one of the public cloud networks like AWS, Azure and GCP. Leverage technologies such as Kubernetes, Helm, Terraform, and Istio to achieve infrastructure resilience. Drive the automation of infrastructure tasks, from provisioning to configuration management and deployment, utilizing tools like Terraform, Ansible, a

awsazuregcp
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E(
1mo ago

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat

pythonsqlaws
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About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. About the Role As a Site Reliability Engineer at Ema, you will own the stability, availability, and operational health of our agentic AI platform across customer environments. You'll work closely with Engineering and DevOps to provision infrastructure, drive deployment excellence, and keep production running at the quality bar our enterprise customers expect — 99.9%+ uptime, proactive incident response, and continuous improvement. What You'll Do Infrastructure & Deployment Design and provision cloud infrastructure (GCP, Azure, AWS) tailored to customer environments, with security, scalability, and compliance built in Execute on-call SaaS deployments with minimal downtime; automate and optimize deployment workflows end-to-end Production Stability & Observability Monitor logs, alerts, and metrics to maintain SLA commitments and catch issues before they escalate Diagnose and resolve production incidents with speed and rigor; drive root cause analysis and permanent fixes Collaborate with DevOps to enhance monitoring dashboards and alerting frameworks; deliver clear system health reporting to internal and customer stakeholders Documentation & Knowledge Management Maintain de

awsazuregcp
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About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning

pythonsqlaws
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Gitlab
📍 Bengaluru• Full-time
1mo ago

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An Overview of this role We are looking for a Senior Release Engineer to help design, standardize, and operate reliable enterprise application delivery across the Enterprise Technology & AI team. This role will establish scalable CI/CD practices for business-critical platforms such as Salesforce, Zuora and other Business Systems while enabling engineering teams to ship changes safely, quickly, and with clear operational controls. The ideal candidate combines strong release engineering and automation skills with practical experience supporting enterprise SaaS applications. You will build and maintain GitLab CI/CD or comparable

pythonci/cdgit
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Gitlab
📍 United States• Full-time• Remote
1mo ago

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An Overview of this role We are seeking a Staff Product Manager to serve as an internal PM embedded within this team. This is not a traditional external-facing product role—it is an internal platform product leadership position. You will own the roadmap for our enterprise systems, act as the strategic voice of the business within engineering, and bring senior product craft to a team of Analysts and engineers who build and operate GitLab's revenue infrastructure. This role is ideal for a seasoned product leader who has deep Quote-to-Cash or Finance domain knowledge, thrives at the intersection of business strategy and techni

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