Cloud Partner Solutions Engineer Jobs

What you’ll do Own and evolve the Quality Management System (QMS) to support a regulated medical device development program, including design controls and DHF maintenance. Establish and enforce requirements traceability: user needs → design requirements → verification/validation artifacts and change control. Define and run the program-level V&V strategy (verification, validation, and test coverage), including test plans, protocols, reports, and acceptance criteria. Drive risk management activities (e.g., DFMEA / PFMEA, hazard analyses) and ensure mitigations are reflected in requirements and verification. Lead document control: reviews, approvals, training, retention, and audit readiness. Partner with engineering to make quality “native” to the dev workflow (automated testing, release gates, software configuration management). Prepare the program for audits and inspections, including hands-on audit leadership. What we’re looking for Senior experience leading quality for complex hardware + software products in a regulated environment. Deep familiarity with design controls, DHF, document control, risk management, and verification planning. Strong systems thinking and the ability to translate ambiguous product intent into testable requirements. Comfortable collaborating directly with multidisciplinary engineering (recon/ML, embedded, mechanical, EE, cloud). Useful experience Regulated product quality leadership (ISO 13485 / 21 CFR 820 or equivalent), including audit readiness and FDA-facing work. eQMS + document control fluency (e.g., Greenlight Guru) that integrates cleanly with modern engineering workflows.

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Hardware Operations Engineer to serve as the technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our datacenters 5 days pe

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 200+ public data centers globally and thousands of private sites 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 You will combine deep SaaS GTM domain knowledge with experience defining decision-grade signals for direct sellers, and partner with engineering to bring them to life as AI agents. In this role, you will identify where reps and sales leaders need real-time signals, and work with engineering to build and prioritize the roadmap for how AI-generated signals power seller decisions across the direct sales motion. What You'll Do (Role Expectations) Partner with Sales and RevOps leadership to identify where reps rely on gut feel, and define signals (deal risk, expansion opportunity, churn risk, next-best-action, account prioritization) that convert raw GTM data into decisions reps can act on Own the signals repository covering business logic, inputs, owner, and status for every signal in the direct sales motion, as the single source of truth for GTM and engineering Partner closely with engineering through build and iteration,

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. What You’ll Be Doing Design, build, and operate highly scalable, reliable, and secure infrastructure powering our production systems across AWS and GCP. Lead major reliability and modernization initiatives, including container platform migrations (e.g., ECS to EKS/GKE) and microservice enablement across multi-cloud environments. Serve as a technical authority in Kubernetes (EKS and GKE), cloud infrastructure (AWS and GCP), and modern CI/CD practices (GitOps, automation pipelines). Partner with development teams to architect and enable microservice-based applications, ensuring production readiness, scalability, and observability. Implement and manage infrastructure as code (Terraform, Ansible) to automate provisioning, scaling, and configuration management across multiple cloud providers. Drive improvements in observability, performance, and cost efficiency through robust monitoring, logging, and alerting systems that span AWS and GCP. Champion SRE best practices — defining SLOs/SLIs, conducting blameless postmortems, and continuously improving incident response. Lead complex technical projects from conception to completion, managing timelines, and technical dependencies across teams. Mentor engineers across teams, fostering a culture of reliability, automation, and continuous learning. Collaborate with security and compliance partners to ensure infrastructure adheres to best practices and standards (e.g., IAM Federation, Workload Identity). Participate in t

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. What You’ll Be Doing Design, build, and operate highly scalable, reliable, and secure infrastructure powering our production systems across AWS and GCP. Lead major reliability and modernization initiatives, including container platform migrations (e.g., ECS to EKS/GKE) and microservice enablement across multi-cloud environments. Serve as a technical authority in Kubernetes (EKS and GKE), cloud infrastructure (AWS and GCP), and modern CI/CD practices (GitOps, automation pipelines). Partner with development teams to architect and enable microservice-based applications, ensuring production readiness, scalability, and observability. Implement and manage infrastructure as code (Terraform, Ansible) to automate provisioning, scaling, and configuration management across multiple cloud providers. Drive improvements in observability, performance, and cost efficiency through robust monitoring, logging, and alerting systems that span AWS and GCP. Champion SRE best practices — defining SLOs/SLIs, conducting blameless postmortems, and continuously improving incident response. Lead complex technical projects from conception to completion, managing timelines, and technical dependencies across teams. Mentor engineers across teams, fostering a culture of reliability, automation, and continuous learning. Collaborate with security and compliance partners to ensure infrastructure adheres to best practices and standards (e.g., IAM Federation, Workload Identity). Participate in t

Coder is looking for an Enterprise Account Manager to grow our diverse customer base. You’ll help bring Coder’s platform to some of the largest companies in the world, who are focused on executing AI-centric software development at scale. This role is about building trusted relationships, shaping deals, and making sure enterprise customers clearly see the value we deliver. Day to day, you will manage the full sales cycle, from sourcing opportunities to closing contracts. You’ll work side by side with engineers, buyers, and internal partners to remove friction and move complex deals forward. What you’ll do here Build and close a strong pipeline of enterprise accounts with large engineering organizations Generate qualified opportunities through outbound prospecting and inbound leads Lead compelling demos that differentiate Coder, and communicate our value with clarity and conviction Collaborate with Sales Engineers to deliver a thorough technical evaluation Partner with decision-makers and technical stakeholders throughout the sales cycle Travel as needed to support deals and customer relationships What we’re looking for Currently based in California 5+ years in software sales with a strong prospecting background (ideally Developer, Agent, DevSecOps, or Cloud Native Computing Foundation (CNCF) technologies) 3+ years selling into Fortune 500 companies Experience engaging with software engineering leaders and technical decision-makers Understanding of DevOps, CI/CD, platform engineering, and developer tools Experience with GenAI & Agentic development tools (Cursor, Claude, Windsurf, Goose, Copilot, etc) Comfortable with outbound motion and partnering with Sales Engineers Track record of exceeding quota and pipeline goals Strong communication skills - written, verbal, and in presentations Familiarity with different sales cycles (startup, midsize, enterprise) Creative, analytical, and highly self-motivated Ability to travel up to 15% Bonus tacos if you have A technica

We are Datadog's in-house product experts. The Datadog Federal Support Engineering team is dedicated to serving as highly trusted technical advisors for our Public Sector customers, who operate within some of the most highly regulated and security-constrained environments. These customers include various government agencies and organizations with critical, sensitive missions. As a Federal Support Engineer 3, this role places you at the forefront of supporting these customers' mission-critical workloads. These complex workloads are often deployed across sophisticated hybrid and multi-cloud architectures, requiring deep expertise in cloud technologies, monitoring, and security best practices. Your primary responsibility is to ensure the complete success of these customers across their entire lifecycle with Datadog. Whether you’re looking to learn from the best or be the best, the Federal Support team is dedicated to furthering personal development and team success. 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: Engage with public sector customers via multiple channels (ticketing system, live chat, calls, and screensharing tools) to identify and resolve technical support requests. Troubleshoot, investigate, and resolve complex technical issues in highly constrained environments across Datadog's 1000+ integrations, often with limited logs or sanitized data. Handle urgent escalation cases that may result in customer-facing troubleshooting calls, and internal or external incident management Become a subject matter expert in many Datadog product areas Partner with Product, Engineering, and Account teams to to validate bugs and advocate for customer-impacting improvements Provide mentorship to junior members of the team and serve

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. We are looking for a Software Engineer II to join the Auth0 Security Engineering organization. You'll help build and maintain the security guardrails for our multi-cloud environment, implementing security and compliance standards as programmatic, code-driven policies. What You Will Do Cloud Security Controls: Implement and maintain organization-wide controls (SCPs, Azure Policy) balancing protection with developer experience. Identity & Access Management (IAM): Build and update templates and permission boundaries that govern how services and humans interact with our cloud, applying the principle of least privilege. Infrastructure & Network Security: Contribute to the security standards for VPC architecture, edge networking, and cross-account connectivity. System Design: Help build systems and processes that validate the security posture of the platform, enforcing our security policies and surfacing actionable feedback for engineering teams. Growth & Collaboration: Partner with teammates across the organization, share what you learn, and continually deepen your security expertise. What You Bring Cloud & Infrastructure Experience: 3+ years of experience in software engineering or information security, with hands-on exposure to cloud-native environments, Kubernetes (EKS, AKS), and cloud security concepts. Policy & Automation: Experience building or maintaining automated controls and infrastructure-as-code, ideally within Terraform workflows

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The mission of the Engineering TPM team is to drive Figma's most important cross-company engineering efforts, and we are looking for a Technical Program Manager (TPM) to partner with our Infrastructure team. The TPM provides oversight of the most important efforts that require coordinated technical execution across the Org to succeed. This is a role focused on enabling Figma's infrastructure teams to scale, improve performance, and deliver on critical projects. These large-scale efforts will involve collaboration across numerous backend, infrastructure, and security teams and cross-functional stakeholders, prioritization, decision-making, tracking execution, and driving operational excellence. We're looking for someone that can work in a TPM greenspace environment and is passionate about people, technology, and program management. Progress over process is our mantra. This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Lead the execution, coordination, and risk management of Figma's infrastructure projects, ensuring seamless integration with minimal performance impact Drive key infrastructure initiatives, including reliability, storage, distributed systems, cloud-native performance improvements, and compliance programs (e.g., encryption key management, FedRAMP, SOC 2) Partner closely with engineering, security, compliance, and legal teams to ensure alignment and on-time delivery Track program milestones and ensure seamless d

Staff Software Integrations Engineer (Fullstack) Position Overview : As a Staff Fullstack Integrations Engineer, you will be a technical North Star for the newly formed internal Integrations team. You aren't just building integrations and plus-ins; you are designing, architecting, and governing the resilient back end services that connect the Showpad platform with leading SaaS ecosystems, and distributed at a global scale. You will partner with product and engineering leadership to bridge the gap between business strategy and technical execution, and be the primary technical gatekeeper, ensuring all backend architectures meet our stringent enterprise standards for security, scalability, and observability. This role is designed for a visionary who balances deep-dive coding with high-level system design and the mentorship of emerging talent. Key Responsibilities: Architectural Stewardship: Author Architecture Decision Records (ADRs) for all major integrations and platform decisions, ensuring alignment with event-driven, asynchronous, and cloud-native principles across the organization. Backend Engineering: Design and build isolated, decoupled microservices in TypeScript and Go that serve as the reference standard for correctness, performance, and maintainability. Frontend Engineering: Define the frontend standards and component architecture for Showpad's integration surfaces — owning patterns for how integration configuration, connection status, and data flows are built across the platform, and ensuring complex backend behaviour translates into experiences that are intuitive and built to last. Cloud Infrastructure: Own infrastructure-as-code practices using AWS CDK across multi-region environments. Make authoritative decisions on data store selection and configuration across DynamoDB and Aurora RDS. Resiliency & Eventing: Build highly idempotent outbound APIs with exponential backoff algorithms. Architect strictly asynchronous webhook ingestion pipelin

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for an Engineering Manager to lead our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. This is a foundational role: you'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes analytics capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. As model capabilities and usage grow, you'll also drive how we scale review through automation — building systems where Claude meaningfully extends what human reviewers can do, while keeping people in the loop where their judgment matters most. You'll partner closely with policy, operations, data science, and legal teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities Lead, grow, and develop a team of engineers building investigation, review, and enforcement tooling for both first-party and third-party platform surfaces Define the vision and roadmap for our review tooling platform, including analytics, privacy-compatible data access primitives, and a sandbox for rapidly developing new review interfaces Drive the team's strategy for scaling review through a

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit