Staff Platform Infrastructure Engineer Jobs

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 We are looking for a Staff DevOps / Platform Engineer to join our team. This is a Hybrid (3 days a week on-site in Mohali) role, reporting to the Director, Product Revenue in the Product Operations department. This individual contributor role owns DevOps, AWS infrastructure, release reliability, security hygiene, and platform maintainability for a business-critical internal platform while leveraging practical AI-assisted development workflows to improve delivery speed and quality. What you’ll do (Role Expectations) Own DevOps, CI/CD, deployments, monitoring, logging, production support, and operational reliability for an existing business-critical internal platform Manage and improve AWS infrastructure using Terraform, including secure access controls, integrations, secrets practices, and infrastructure hygiene Ensure weekly releases are safe through testing, rollback planning, monitoring, post-release che

P-1930 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI. The Foundation Model Inference team is the backbone of Databricks’ generative AI capabilities. We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance. Our Foundation Model APIs provide a unified platform that gives customers access to LLMs with the governance, flexibility, and scalability required for enterprise production workloads. We are looking for high-agency engineers who are excited to work on powering model inference at enterprise scale. Check out our recent blog post: Reliable LLM Inference at Scale The impact you will have: Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and sel

P-1549 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. The Mission Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds. We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers . This is a zero-to-one role with two deeply connected charters: Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems. Build the search subagents that sit on top of that stack and reason about what context is needed , how to retrieve it , and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it. If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you. What You Will Do Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come. Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queri

P-1605 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role At Databricks, we don’t just use the cloud; we are "cloud maximalists." Unlike most companies that treat multi-cloud as a backup strategy, we run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously. This creates a massive, high-consequence engineering surface area that requires a unique breed of Production Engineer. In this role, you won’t just run our cloud environments; you will own and evolve the secure infrastructure, access patterns, and guardrails that keep Databricks’ global platform safe and compliant in production. You will be responsible for the "sovereign layer" of our infrastructure, ensuring that our Data Intelligence Platform operates with 100% reliability and security in highly regulated, air-gapped, and sovereign environments. If you are an engineer who views infrastructure as a software problem and thrives on the complexity of global-scale networking, IAM, and automation, this is your team. The Impact You’ll Have Security-Focused Cloud Operations Design, automate, and operate the IAM, account/subscription, and project lifecycle across AWS, Azure, and GCP, enforcing least-privilege and standardized access patterns at scale. Review, implement, and continuously improve cloud identity and access policies (IAM, Okta, Opal) to align with Data

P-1603 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role At Databricks, we don’t just use the cloud; we are "cloud maximalists." Unlike most companies that treat multi-cloud as a backup strategy, we run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously. This creates a massive, high-consequence engineering surface area that requires a unique breed of Production Engineer. In this role, you won’t just run our cloud environments; you will own and evolve the secure infrastructure, access patterns, and guardrails that keep Databricks’ global platform safe and compliant in production. You will be responsible for the "sovereign layer" of our infrastructure, ensuring that our Data Intelligence Platform operates with 100% reliability and security in highly regulated, air-gapped, and sovereign environments. If you are an engineer who views infrastructure as a software problem and thrives on the complexity of global-scale networking, IAM, and automation, this is your team. The Impact You’ll Have Security-Focused Cloud Operations Design, automate, and operate the IAM, account/subscription, and project lifecycle across AWS, Azure, and GCP, enforcing least-privilege and standardized access patterns at scale. Review, implement, and continuously improve cloud identity and access policies (IAM, Okta, Opal) to align with Data

P-1604 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role At Databricks, we don’t just build software for the cloud; we are "cloud maximalists." We run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously, creating a technical surface area that is unique in the industry. As a Software Engineer on our Public Sector team, you will be responsible for the core backend engineering that allows our Data Intelligence Platform for the Public Sector to operate at massive scale within sovereign and air-gapped cloud environments. We are looking for world-class Software Engineers to join our core Backend Engineering teams. You will design, build, and scale the distributed systems that power one of the largest data and AI infrastructures in the world. You will tackle high-scale infrastructure challenges where "zero-waste" compute efficiency and 100% system resilience are mandatory. From optimizing massive data storage layers to architecting low-latency microservices that must function in disconnected regions, you will own the end-to-end lifecycle of mission-critical code. The Impact You’ll Have Architect Scalable Systems: Design and implement highly available backend services using Scala, Java, Go, C++/C or similar . Distributed Systems Engineering: Design and implement highly scalable backend services in Java, Scala, or Go

NVIDIA is seeking a Senior Staff SRE to build and operate reliable, scalable compute platforms that support global engineering workloads. This role spans Kubernetes, KubeVirt, bare-metal infrastructure, automation, observability, and AI-enabled operations. Join a team that solves complex infrastructure challenges, builds durable automation, and improves the reliability and operational experience of critical compute services. What you’ll be doing: Build, operate, and improve large-scale Kubernetes, KubeVirt, Linux, container, and bare-metal compute platforms, with a focus on performance, capacity, reliability, and operational scale. Lead bare-metal provisioning and lifecycle management in data centers, including PXE boot, DHCP, DNS, OS provisioning, hardware validation, and fleet automation. Develop automation, self-service capabilities, and observability solutions using APIs, Python or Go, Infrastructure as Code, configuration management, metrics, logs, traces, and service-health data. Define and operate SLOs, SLIs, error budgets, alerting, and incident-response practices; lead complex incident investigations, corrective actions, and blameless postmortems. Partner with infrastructure, security, hardware, data-center, and application teams to deliver global platform initiatives, and participate in an on-call rotation. What we need to see: BS in Computer Science, Engineering, a related technical field, or equivalent experience, plus 10&#43; years operating production infrastructure or platform services. Strong expertise in Kubernetes administration, KubeVirt, Docker, containerization, microservices, Linux systems, and resolving distributed-system challenges. <l

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Overview We are looking for a strong software and platform engineer to join our Production Engineering team in Bangalore as an individual contributor in FA ProductionEng APJ. This role will help build and operate internal platforms that improve how we provision, observe, govern, and troubleshoot engineering infrastructure at scale. The fleet management use cases that give teams a single place to understand and operate the test infrastructure. If you enjoy building internal platforms that remove friction, improve visibility, and make engineering teams faster and more effective, this role is for you. Why This Role Is Unique This is not a typical application development role.You will work on internal platforms that directly shape how engineering teams consume and manage shared infrastructure. The role spans platform engineering, workflow automation, observability, API-driven services, and infrastructure lifecycle management. The right candidate will work on systems such as: Self-serviceability workflows and lease-based testbed governance. Developer Platform dashboards and APIs used for triage, visibility, and product trend observation. Testbed and workflow orchestration across fleet management domains. Impact This role is a high-leverage engineering investment. The work will improve how engineering teams provision testbeds, understand failures, operate shared infrastructure, and move faster with less friction. Better

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Lakebase enables teams to deliver applications faster with an optimized database developer experience, integration with the lakehouse, and simplified operations. It provides a managed Postgres transactional layer for application state and workloads that combine operational data, analytics, and AI. You'll join as one of the key engineers building out the Lakebase product. As the Technical Lead on the Lakebase Manager (LBM) team, you will drive, build, and operate the central control plane that owns the core logic for Lakebase: database creation and deletion, wake-up and suspend, maintaining computes on hot standby, HA failover, and more. LBM interacts with every Lakebase component (storage, compute, proxy, and console) and manages the full database lifecycle at scale, with a focus on reliability. This is a hands-on individual-contributor role: you lead the team technically and partner with the team's engineering manager, who owns people management and delivery planning. The stack is Go, Rust, PostgreSQL, and Kubernetes. The impact you will have: Set the technical direction for LBM and own the quality and reliability of what the team ships, driving execution on the hardest, highest-risk parts. Drive architecture and design, and write code on the hardest parts of your team's projects. Set and uphold high technical standards through a

RDQ427R371 At Databricks , we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role We're seeking a Partner Engineer to own the technical relationship between Databricks Product/Engineering and Microsoft Azure. You will be the primary technical liaison managing our cross product roadmap, driving engineering integrations, and ensuring Databricks products work seamlessly within the Azure ecosystem. You will work directly with Azure Partner SAs, Product Managers, and engineering teams to align roadmaps, identify integration gaps, and accelerate feature delivery. This role reports to the Director of Partner Engineering and works closely with Databricks Product Management, Engineering, and Field teams. Impact you will have Own the Databricks-Azure product-to-cloud technical roadmap, serving as the primary interface between Databricks Product Management and Azure partner teams to ensure alignment on features, integrations, and co-innovation priorities. Track and drive resolution of cross-company dependencies and blockers, manage joint milestone timing with Azure teams, and own the coordination rhythms (recurring syncs, escalation paths) that keep both sides aligned through delivery. Drive engineering integration work between Databricks and Azure product teams coordinating cross-company technical initiatives from scoping through delivery. Create and maintain technical architecture a

Job Title: Senior Staff Software Engineer - Enzyme Location: Mountain View, California --------------------------------- P-1183 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. The Lakeflow Engineering team here at Databricks is responsible for the entirety of the ETL product line. This includes products such as Materialized Views, Structured Streaming, and Delta Live Tables. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers. We're seeking a dedicated technical leader to spearhead the Materialized Views engineering team. The team is responsible for building next generation Materialized View features for both ETL workloads and for query acceleration. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Incrementally maintaining materialized views Query optimization Resource management Efficient storage structures Automatic physical data optimization The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant architecture for materialized views Low level systems debugging, performance measurement & optimization on large production clusters. Build architecture design, influence product roadmap, and take ownership and responsibility over new projects. Introduce tools to allow greater automation and operability of services. Use your deep experience to help prevent and investigate production issues.

P - 1381 At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Team The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams. As a Staff Backline Engineer, you will be a technical expert and escalation point for some of the most complex ML/AI issues. You will work across Support, Engineering, Product, and customers to troubleshoot difficult problems, reproduce issues, identify root causes, and drive them to resolution. What You'll Do Serve as a senior escalation point for complex ML/AI issues involving model training, inference, Model Serving, MLflow, Feature Engineering, with knowledge of Spark, Delta Lake, and distributed workloads. Perform deep technical investigations using logs, traces, metrics, profiling, configu

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure

Staff Software Engineer - Money Team P-940 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructu