Cloud Platform Engineering Jobs

P-78 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. As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. The impact you'll have: Our backend teams span many domains, from our core compute fabric resource management infrastructure, to service platforms, to machine learning infrastructure. For instance, you might work on challenges such as: Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way Develop reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers Build tools to allow Databricks engineers to operate their services across different clouds and environments Build services, products and infrastructure at the intersection of machine learning and distributed systems. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes. Experience with security and systems that handle sen

P-78 While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered. 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. As a Senior Software Engineer on the Infrastructure teams, you will build scalable systems to power the Databricks platform, making it the de-facto platform for running Big Data and AI workloads. You will build and extend the Databricks infrastructure platform, which includes multi-cloud systems and services for managing thousands of Kubernetes clusters at scale, storing petabytes of data, highly scalable and distributed API gateways, rate limiting framework, network security and encryption, developer tools and infrastructure (we use Bazel), testing frameworks, and scalable CI/CD framework among many others. The impact you will have: Build and extend components of the core Databricks infrastructure Architect multi-cloud systems and abstractions to allow the Databricks product to run on top of existing Cloud providers Improve software development workflows for engineering and operational efficiency. Use our own data and AI platform (yes!) to analyze build and test logs and metrics to identify areas for improvement. Develop automated build, test, and release infrastructures. Set and uphold the standard for engineering processes to support high-quality engineering, including style and code checking, test harness

P-275 While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in various cities around the US. At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world! The impact you will have: Develop customer engagement strategies in partnership with Account Executive(s) in your designated territory. Coach junior Solutions Architects and teams on use case prioritization and building technical champions. You will influence stakeholders at all levels through complex engagements with the wider cloud ecosystem and 3rd party applications, ensuring they are excited by the Databricks vision and solution strategy. Be a 'champion’ for both customers and colleagues, operating as an expert solution architect and trusted advisor for significant data analytics architecture, design, and adoption of the Databricks Data Intelligence Platform. Contribute to Databricks' technical community engagement by developing customer-facing collateral and leading workshops, seminars, and meet-ups. Opportunity

P-273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and our users Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community. What we look for: 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in, and debugging, Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies ( Ex: Spark, Hadoop, Kafka ) Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, pytorch, Tensorflow ) Avai

P-78 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. As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. The impact you'll have: Our backend teams span many domains, from our core compute fabric resource management infrastructure, to service platforms, to machine learning infrastructure. For instance, you might work on challenges such as: Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way Develop reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers Build tools to allow Databricks engineers to operate their services across different clouds and environments Build services, products and infrastructure at the intersection of machine learning and distributed systems. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes. Experience with security and systems that handle sen

P-57 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 Intelligence 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 Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products. The impact you will have: Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights. Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations a

Sigmoid empowers enterprises to make smarter, data-driven decisions by blending advanced data engineering with AI consulting. We collaborate with some of the world’s leading data-rich organizations across sectors such as CPG-retail, BFSI, life sciences, manufacturing, and more to solve complex business challenges. Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in Bengaluru and operations across the USA, Canada, UK, Netherlands, Poland, Singapore, and India. Recognized as a leader in the data and analytics space, Sigmoid is backed by Peak XV Partners and has consistently received accolades for innovation and rapid growth. Highlights include being named a ‘Leader’ in ISG’s Specialty Analytics Services for Supply Chain (2024), a two-time ‘India Future Unicorn’ by Hurun India, and a four-time honoree on both the Inc. 500 and Deloitte Technology Fast 500 lists. Technical Lead – Data Engineering As a Technical Lead, you will be responsible in building a highly-scalable and extensible big data platform that provides the foundation for collecting, storing, modeling, and analyzing massive data sets from multiple channels. This position reports to Engineering Manager. Responsibilities: Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Connect with VP and Director level clients on a regular basis. Travel to client locations Ability to understand business requirements and tie them to technology solutions Facilitate in Technical Aspects Design, develop and evolve highly scalable and fault-tolerant distributed components using Big data technologies. Excellent experience in Application development and support, integration development and data management. Provide technical leadership and manage it day to day basis Guiding developers

P-59 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. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Data Plane Storage : Provide reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Delta Lake : A storage management system that combines the scale and cost-efficiency of data lakes, the performance and reliability of a data warehouse, and the low latency of streaming. Its higher level abstractions and guarantees, including ACID transactions and time travel, drastically simplify the complexity of real-world data engineering architecture. Delta Pipelines : It's difficult to manage even a single data engineering pipeline. The goal of the Delta Pipelines project is to make it simple and poss

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lake using open formats like Apache Iceberg, delivering deep correlation and long-term analytics at dramatically lower cost. A dynamic Knowledge Graph and chat-based AI SRE provide rich context and guided workflows so teams can move from detection to root cause and resolution significantly faster. The Infrastructure team at Observe by Snowflake is responsible for building, scaling, and operating the development and production environments that power our observability platform. We are a small, highly collaborative team with a broad scope, focused on delivering reliable infrastructure while continuously improving the systems that support our engineers and customers. We’re looking for dedicated students who share our passion for ground-breaking technology and want to create a lasting future for you and Snowflake. WHAT WE OFFER : Paid, full-time internships in the heart of the software industry Post-internship career opportunities (full-time and/or additional internships) Exposure to a fast-paced, yet fun, startup culture A chance to work with world-class experts on challenging pr

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, norma

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 Staff Software Engineer on the FinHub - Transfers team within the Platform group, you'll own the architectural direction of the systems that power crypto and fiat fund movements across Coinbase. The Transfers team builds one of the most critical and high-scale distributed financial platforms in the industry, enabling fund movement for Retail, Prime, Exchange, International, and Payments products. You'll make key technical decisions, drive platform reliability and scalability improvements, and lead cross-functional initiatives that directly impact how millions of customers move money on Coinbase. What You'll Do: Own the technical architecture of Transfers' fund movement systems, driving design decisions on distributed system structure, correctness guarantees, and scalability across crypto and fiat rails Lead complex, cross-team engineering initiatives end-to-end, partnering with Payments, Trading, and product engineering teams to deliver new fund movement capabilities and platform improvements Drive the evolution of Transfers' backend infrastructure using modern cloud-native patterns, proactively identifying scaling bottlenecks and architecting solutions before they impact customers Establish engineering standards, code review practices, and architectural patterns that raise the quality bar across the team and reduce operational risk in high-correctness financial

About the Role As a Hardware Security Engineer, you’ll contribute to building open, transparent, and secure AI systems. You’ll have the opportunity to work on projects that safeguard corporate assets by implementing and operating preventative and reactive security controls while collaborating with teams and stakeholders across the company. We’re looking for an intern that is interested in building AI-assisted security apps. Responsibilities Design, prototype, and implement security solutions for AI infrastructure across hardware, firmware, operating systems, and cloud services, including BMCs, TPMs, secure boot chains, networking interfaces, and workload identity systems. Assess and improve the security posture of server and accelerator platforms, including firmware update processes, device identity, trusted execution, and hardware-backed cryptography. Support the secure platform lifecycle, from device onboarding, provisioning, and inventory through configuration validation and decommissioning. Build automation and internal tools in Python, Bash, or similar languages to collect platform telemetry, detect configuration drift, and support incident investigation. Build AI-assisted security applications for asset classification, anomaly detection, and detection-and-response workflows. Partner with IT and infrastructure teams to implement and enforce identity, access-control, endpoint, and privileged-access security practices. Research and evaluate emerging technologies such as confidential computing, remote attestation, hardware roots of trust, and secure device management. Write clean, well-documented code, technical designs, test plans, and security findings. Requirements Actively pursuing a degree in Electrical Engineering, Computer Science, Software Engineering, or a related field expected by Summer 2027 Foundational understanding of computer architecture, operating systems, networking, embedded systems, digital logic, or electronics Strong programming skills

Who are we? FalconX is a pioneering team of operators, investors, and builders committed to revolutionizing institutional access to the crypto markets. Operating at the intersection of traditional finance and cutting-edge technology, FalconX addresses the industry's foremost challenges: Navigating the digital asset market can be complex and fragmented, with limited products and services that support trading strategies, structures, and liquidity found in conventional financial markets. As a comprehensive solution for all digital asset strategies from start to scale, FalconX operates as the connective tissue empowering clients with seamless navigation through the ever- evolving cryptocurrency landscape. Responsibilities Build, scale, and optimize core low-latency trading platforms. Architect AWS and hybrid cloud infrastructure for microsecond execution using kernel tuning (isolcpus), AWS Placement Groups, and enhanced networking (ENA/ENI). Design and maintain release pipelines for core trading engines (OMS, EMS, Gateways), ensuring zero-downtime deployments and deterministic rollbacks. Collaborate across teams to enhance platform reliability, performance, scalability, and security. Provision high-throughput messaging paths (Aeron, FIX gateways) to support venue expansions for market making and regional growth. Drive infrastructure automation, network topology design, and OS configurations using Terraform and Ansible. Build real-time telemetry pipelines using Grafana Cloud, Alloy, and Prometheus to detect latency spikes and system issues. Drive continuous platform efficiency, reduce tick-to-trade latency, and accelerate deployment cycles. Practice sustainable incident response, reduce MTTR, establish error budgets, and conduct blameless postmortems. Share on-call rotation duties and serve as a primary escalation point for production incidents. Enforce security best practices across all trading infrastructure to minimize attack surfaces and guarantee data integrity. Min