Staff Production Engineer in United States

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. Production Engineer to join our team. This role is available as a hybrid opportunity 3 days a week in San Jose, CA or Remote reporting to Production Engineering in the Cloud Infrastructure & Operations department. Join Zscaler to be a force multiplier for the reliability of a global platform processing 200+ billion transactions daily across tens of millions of enterprise users. In this role, you will provide the technical vision and hands-on execution to drive an "automation-first" culture across the company. By maturing our observability and architectural standards, you will directly reduce our Mean Time to Mitigate (MTTM) and shape the scalability of our globally distributed, multi-cloud infrastructure. What you’ll do (Role Expectations) Implement highly available, scalable infrastructure across AWS, GCP, and bare-metal environments Drive an "automation-first" culture by wr

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Principal Security Software Engineer on the Production IAM team, you will set the technical direction for how identity and access work across Roblox's production infrastructure, from the mTLS-based identity that services use to authenticate to one another, to the privileged access controls that govern how engineers reach production. The team is accountable for Roblox's machine and workload identity platform, its centralized authorization engine, its production access management platform, production PKI and certificate lifecycle, and just-in-time privileged access for engineers. As an individual contributor in Production IAM, you will define multi-year strategy, drive alignment across Roblox Platform, mentor senior and staff engineers, and personally build the hardest parts of these systems. As AI agents become first-class actors in production, you will also help pioneer how they get identity, prove who they are, and receive safely-scoped access. You will Lead the architecture for production identity and access. Define and evolve the end-to-end design for machine, workload, human, and AI-agent identity across our hybrid on-prem and cloud fleet, making secure access invisible when

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer – AI Product to join our ClickUp Engineering team. In this role, you will drive the development of intelligent, user-facing features that leverage the latest advancements in AI and large language models (LLMs). You will work closely with product, design, and engineering teams to deliver seamless, impactful AI-powered experiences that delight our users and differentiate ClickUp in the productivity space. This is a product-focused engineering role requiring deep expertise in AI, LLMs, and building scalable, production-ready applications. Key Responsibilities: Lead the design, development, and deployment of AI-powered features and products that directly impact ClickUp users. Collaborate with product managers, designers, and engineers to identify opportunities for AI-driven innovation and translate user needs into technical solutions. Integrate and orchestrate multiple LLMs and AI models to deliver robust, context-aware, and personalized user experiences. Prototype, test, and iterate on new AI features, leveraging user feedback and data to drive continuous improvement. Ensure the reliability, scalability, and performance of AI-powered features in production environments. Stay at the forefront of AI research and product trends, incorporating the latest advancements into ClickUp’s product roadmap. Address AI privacy, security, and compliance challenges, ensuring responsible and ethical use of AI in user-facing applications. Mentor and guide other engineers in best practices for building AI-powered products. Qualifications: Proven experience bui

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay current with ad

Manufacturing Test Engineer – Server Hardware Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. Role Overview We are seeking an experienced Manufacturing Test Engineer to support high-volume server manufacturing from board-level test through system-level production test. This role will work closely with an ODM manufacturing partner to define, implement, validate, and optimize the manufacturing test strategy for L6 board-level products , including ICT, MDA, and Board Functional Test , as well as support L10 system-level manufacturing test . The ideal candidate has strong experience in server hardware manufacturing, Linux-based test environments, diagnostic test coverage, fixture requirements, yield improvement, and root cause corrective action processes. This role requires both technical depth and hands-on manufacturing execution experience, with the ability to drive best practices across test development, factory readiness, quality planning, and ongoing production support. Key Responsibilities Manufacturing Test Strategy and Planning Work with ODM partners to define and execute the manufacturing test strategy for L6 board-level production . Develop and review test plans covering: In-Circuit Test, or ICT Manufacturing Defect Analyzer, or MDA Board Functional Test Diagnostic coverage requirements Manufacturing line test flow Fai

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. We believe Plaid has the power to be the next-gen Credit Bureau - supporting large scale adoption of cash flow into the credit underwriting process. The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers. We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly. You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap. You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions. Responsibilities: Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training. Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors

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

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. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. 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: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, cloud services, mechanical engineering, electrical engineering, and product design to deliver reliable, production-ready devices at scale. Within Consumer Devices, Hardware Engineering eXperience, or HEX, is a new bootstrapped team building the environments, applications, compute, product-data systems, and workflows that let hardware engineers do their work without needing to troubleshoot the machinery underneath. HEX owns virtual engineering environments, HPC/GPU compute, storage, networking, licensing, MCAD/ECAD/CAE applications, PLM, product data, automation, validation, and support as one connected system. About the Role As a Staff PLM & Engineering Applications Engineer, you will be one of the first technical builders of HEX and the primary counterpart to the HEX lead. You will own the engineering-application and product-data side of the hardware engineering experience, with an initial focus on NX, Teamcenter, licensing, parts import, integrations, packaging, validation, and user workflows. This is not a traditional Teamcenter administration role and not a Corporate IT application-support role. You will take complex, fragile workflows and turn them into reliable engineering systems. This role is highly hands-on and systems-oriented. You will not inherit a mature environment and support queue. You will help build a fresh one, replacing manual setup guides, tribal knowledge, repeated support issues, and team handoffs with tested automation and reliable workflows. In This Role, You Will Own the technical architecture, deployment, configuration, integration, validation, and long-term operation of NX and Teamcenter. Build reliable workflows for parts import, product-data migration, metadata quality, BOMs, revisions, lifecycle states, and releas

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. Replit is building the world’s most accessible AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it’s an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit builds complete apps better than anybody thanks to our full suite of services that handle app integrations, storage, hosting, analytics, and more. We don’t just build apps in development, we handle the full lifecycle into production and beyond. About the role: Help power the development of Replit Agent as a technical leader for the Replit Cloud organization. You will report to the Vice President of Engineering. The Replit Cloud team builds Replit’s first party cloud infrastructure so users can build, scale, and succeed entirely on Replit. They manage databases, application storage, app publishing and hosting, development/production environment splitting, custom domains, and more. By having a set of first party services that integrate seamlessly, you will power one of Replit’s key product differentiators. You will: Help lead major projects, either by taking new products from 0->1 or doubling down on our first party primitives to keep winning users. Work closely with designers and product managers, to quickly iterate on Replit Cloud to continually grow and improve the product. Identify the hardest technical and/or quality problems holding us back, and then build solutions. Mentor and develop new senior engineers to help grow the team. Ship product and build infrastructure as a true full stack builder using: TypeScript, React, CSS, Postgres, Go, and Terraform. Examples of what you could do: Leverage our unique cloud infrastructure to build diffe

Datadog’s Cloud Networks team designs, builds, and maintains the production network infrastructure that powers everything built on top of our platform across AWS, GCP, Azure, and beyond. In this role, you’ll set technical direction for how we scale our multi-region, multi-cloud network footprint while keeping reliability and performance high. You’ll partner closely with internal teams and Cloud Service Providers to troubleshoot complex connectivity issues, integrate new networking capabilities, and improve the foundations our engineers and customers rely on. This is a high-impact opportunity to drive meaningful improvements in scale, resiliency, and cost efficiency. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design, build, and operate cloud network infrastructure across AWS, GCP, Azure, and Neoclouds in a multi-region environment. Own connectivity between clouds, customers, and developers—ensuring scalable, secure, and reliable network paths. Set clear technical direction for expanding data centers and evolving the network while maintaining stability and performance. Improve cross-site and cross-region connectivity patterns to support Datadog’s growing platform needs. Lead deep investigations into latency, packet loss, and connectivity failures – from pcap and path analysis through to escalations with cloud providers that may originate from customer support Identify and deliver network-related efficiency and cost-saving opportunities that positively impact business health. Who You Are: You have deep networking expertise. You understand BGP, route policies, path selection, prefix advertisement, and what breaks in large-scale networking. You have substantial experience designing, building, and evolving large-scale Software-Defined Networks—inclu

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Staff Software Engineer - Container Platform (Menlo Park) About the Role We build the foundational container platform that runs Snowflake's production, AI/ML, and CI workloads across AWS, Azure, and GCP, including a rapidly growing AI/ML footprint. Hundreds of large Kubernetes clusters under management and growing. The work is to make that fleet reliable, automated, and invisible to the thousands of engineers building on top of it. This is a staff-level role on a senior, high-performing platform team. You'll own hard problems end to end, drive technical direction across teams, and build the automation and platform abstractions that make operating at this scale sustainable. There is significant unsolved work ahead: improving the developer experience for thousands of internal engineers and continuing to scale the platform to meet Snowflake's growth. What You'll Do Own the design and delivery of large, complex platform initiatives spanning cluster lifecycle management, multi-cloud automation, and internal developer tooling. Identify and drive cross-team technical improvements across the platform, from architecture through adoption. Make and defend architectural trade-offs grounded in reliability, scalability, and operational reality. Act as a technical anchor for the team, dev

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.

1743 - This position is in Austin, Texas. Position Summary We are seeking an experienced Board-Level Hardware Validation Engineer to define and execute the validation and verification of complex electronic systems throughout the product lifecycle. This role is responsible for defining validation strategies, developing test plans, executing hands-on testing, analyzing failures, and working directly with ODM partners to ensure products meet performance, reliability, quality, and compliance requirements before mass production. The ideal candidate combines strong electrical engineering fundamentals with practical lab expertise and is comfortable personally performing validation activities while coordinating with cross-functional teams and manufacturing partners. Key Responsibilities Validation Strategy & Planning Define comprehensive board-level and inter-board validation plans based on product requirements, design specifications, and customer use cases. Develop validation methodologies covering functional, electrical, thermal, power, signal integrity, reliability, and stress testing. Establish test coverage, acceptance criteria, qualification requirements, and release gates. Review hardware architecture, schematics, component specifications, and interface topologies to identify validation risks early in the design cycle. Define incremental validation and regression coverage for component substitutions, design changes, and firmware updates. Hands-On Validation Execution Develop, automate, and execute validation tests on prototype and production-intent hardware. Perform board bring-up, functional verification, electrical characterization, and system-level integration testing. Validate communication interfaces, control signals, and timing requirements. Verify power sequencing, reset behavior, leakage current, and recovery across operating states. Execute temperature and voltage corner testing against approved operating limits. Use oscilloscopes, logic an