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 Join the Digital Experience (DX) business unit to deliver the next generation of intelligent, cloud-native fleet management solutions for our customers. You will contribute to our mission of simplifying operations by building scalable SaaS platforms that leverage AI, security, and automation . This role involves working across the full application lifecycle, from Pure IAM to Pure1 Manage , collaborating with cross-functional teams to translate business needs into resilient, production-ready systems. WHAT YOU'LL DO Own the end-to-end design, development, and operation of mission-critical processing services , ensuring seamless, secure, and compliant data flow between edge devices and the Pure1 cloud platform. Partner with Product and Architecture teams to translate complex requirements into scalable, resilient architectural designs that drive significant organizational impact from initial concept through to production deployment. Drive continuous innovation by experimenting with new technologies, platform ecosystems, and architectural patterns to improve system performance, security, and cost-effectiveness for petabytes of real-time data. Maintain a quality-first mindset throughout the entire software development lifecycle, emphasizing comprehensive unit testing, thorough code reviews, and robust Continuous Integration/Continuous Deployment (CI/CD) pipelines. Lead the resolution of complex inter-operab
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CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. Today, CLEAR is well-known as a leader in digital and biometric identification, reducing friction for our members wherever an ID check is needed. We’re looking for a Senior Software Engineer to establish our Observability framework and foundations. You will join us to accelerate building and scaling our innovative systems that support our growing identity platform. You will drive on Observability best practices to find and fix gaps in our observability and our overall systems. You will also lead practices such as load testing, capacity planning, game days, chaos testing, and incident post-mortems. What You Will Do: Embed within the Engineering pillar to deeply understand the product and implement observability across all key flows Facilitate and build load testing cases, ensuring we understand the limits and scaling factors of our services and systems Contribute to observability and support the design of new services and systems, ensuring highly reliable and scalable concepts are implemented Build and lead practices such as game days, chaos engineering, and failure analysis Build long-term capacity plans, with an eye toward reliability and cost-efficiency Who You Are: 6+ experience writing production-grade software in a modern language, such as Java and Python. Strong knowledge of distributed systems concepts (think CAP theorem), microservices architecture, and distributed tracing . Experience with modern observability systems such as Datadog. Experience with performance debugging tools and patterns. You should be able to read a f
Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Our Construction & Engineering team drives the delivery of world‑class facilities that power Micron’s manufacturing and innovation. We work across disciplines to build safe, efficient, and reliable environments that enable teams across the company to do their best work. We are looking for a Project Manager who will lead complex construction projects from concept through completion. In this role, you’ll own scope, schedule, and budget while coordinating multi-functional teams and ensuring that safety, quality, and technical excellence are built into every step. Your leadership will make a direct impact on Micron’s ability to grow and operate at scale. Responsibilities: Lead assigned construction projects, managing scope, schedule, budget, resources, and vendor performance Ensure all work follows Micron safety, environmental, and quality standards; drive proactive hazard identification and resolution Develop and maintain project financials including estimates, forecasts, cash flow, and cost controls Build and manage detailed project schedules; remove roadblocks and coordinate multi-functional alignment Lead design reviews, competitive bidding, contract execution, and project programming and development activities Minimum Qualifications: Degree in Engineering, Construction Management, Project Management, or related field; or relevant certification/licensing 5+ y
About the Role & Team Every AI insight, every experiment, every cohort at Amplitude starts with a query. Our in-house OLAP engine, Nova , processes trillions of events in real time — turning raw behavioral data into fast, trustworthy answers that power decisions for thousands of product teams worldwide. We’re entering a world where AI agents don’t just assist product teams — they ship features, run experiments, and make prioritization calls autonomously. What makes that possible is agents’ ability to verify their work against real product data continuously. That makes Nova the critical infrastructure in the loop, and as non-stop agents become the main source of queries, the demand on Nova’s throughput, correctness, and operational rigor grows dramatically. We’re looking for a Staff Software Engineer who wants to go deep on both the engine internals and the infrastructure underneath it. You’ll work across the full stack of a modern OLAP system — query planning and execution, columnar storage and encoding, distributed compute, caching, and cloud infrastructure — while driving meaningful improvements to performance, cost-efficiency, and reliability at scale. You’ll influence technical direction through your work, your design reviews, and your mentorship of other engineers on a team of ~10. This role is ideal for someone who finds real satisfaction in making a complex distributed system faster, cheaper, and more reliable — and who wants to do that work on a system that directly powers the product experience for thousands of customers. What You’ll Do Build and evolve core query engine infrastructure Work across Nova's query execution engine and distributed compute layer: query planning, columnar storage formats, encoding and compression, caching, and cluster-level resource management. Design and implement new capabilities as Nova expands to support more warehouse-imported data types, such as metrics, profiles, and dimensions. Design for high-throughput automated quer
About The Role & Team Amplitude is only as useful as the data inside it. The Data Connections team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import pipelines onto a durable workflow engine, building low-latency streaming export, and supporting cross-region and cross-cloud customer storage. You'll lead a team of around 10 engineers building this, reporting to our Head of Data Platform, and you'll be the person accountable for the roadmap, the reliability, and the growth of the people on it. The stack is Java, Temporal, Kafka, Kubernetes, Terraform, DynamoDB, S3, and Snowflake, running on AWS and GCP. Responsibilities Set the direction and roadmap for data import and export, with clear priorities and tradeoffs you can explain to engineers, PMs, and customers Lead, coach, and grow a team of around 10 engineers — hiring, career development, feedback, and performance Partner with your tech leads on architecture across ingestion, transformation, and delivery, without becoming the bottleneck for every decision Own reliability, SLOs, and cost efficiency for pipelines customers depend on daily Expand the set of destinations and sources we support, and make each new integration cheaper to build than the last Work directly with Product, Design, and other Data Platform teams to ship e
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist . The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness. This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage. What You’ll Do Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost. Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers. Create and maintain solution architecture artifacts: System context and data flow diagrams Integration plan across Ramp and customer systems Security model covering permissions, access patterns, and au
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: We are seeking talented distributed systems engineers who are passionate about building innovative solutions for application deployment. Your mission will be to enhance the capabilities of Replit Infrastructure, optimize performance across global regions, and drive efficiency while delivering an exceptional user experience. If you have a strong foundation in software development, a deep understanding of cloud technologies, and a track record of delivering high-quality code, we want to hear from you. In this role you will: Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services. Required skills and experience: Distributed systems: Track record of working with platform-as-a-service, distributed storage, o
Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role: As a Senior Manager on the Capital Markets team, you will bridge the gap between business lines and Capital Markets to drive new product development. You will ensure the Capital Markets team is fully positioned to support both new lending products and existing product enhancements. By leading cross-functional initiatives, you will educate potential investors on our offerings, actively manage and develop the investor pipeline, and negotiate term sheets to deliver the scalable funding solutions that fuel our growth. What you’ll do: Partner with business lines to support enhancements to existing products and drive the launch of new lending solutions. Coordinate across internal and external teams to seamlessly integrate new lending products and funding structures. Support investor education and due diligence processes, developing materials and coordinating discussions with external partners and counterparties. Gather and incorporate investor feedback into product design and future enhancements. Negotiate term sheets and maintain investor pipelines. Model product economics, analyze funding efficiency, and assess trade-offs between risk, cost, and complexity. Define requirements to support new products, ensuring infrastructure and reporting are accurate and scalable. Partner cross-functionally to valida
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. Roblox's Cache team is building a next-generation caching solution designed to deliver sub-millisecond average latency, horizontal scalability, and high efficiency—all at a drastically lower cost. Our ultimate vision is to shape a caching infrastructure capable of supporting 1 billion Daily Active Users while reducing costs by 90%. We are turning hours of onboarding and capacity expansion into seconds, freeing service owners entirely from managing cluster lifecycles. As a Senior Engineer on the Cache team (part of the Infra Storage org), you will innovate and operate large-scale, in-house distributed systems to solve Roblox's ever-growing caching challenges. You will report directly to the Engineering Manager for the Cache team. (Check out our recent engineering blog post here to learn more about the team's latest work!) You will: Lead the architectural transition to a next-generation, multitenant caching service built on ValKey, ensuring strict data, resource, and failure isolation for all tenants. Drive systemic optimizations to mitigate head-of-line blocking, manage hot keys, and maximize CPU and memory utilization across physical machine clusters. Design and build robust frameworks to a
Please note that the job is only available from the locations outlined. We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r
As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r
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 . Coinbase’s Consumer Engagement and Experience (CEE) Surfaces team owns the front door to support for millions of customers: help.coinbase.com, social support, and Athena, the knowledge platform used by CX agents. We are rebuilding these experiences to be AI-native, with retrieval, generation, and agentic resolution at the core. We’re hiring an Engineering Manager to lead and scale the team responsible for these surfaces. You’ll set technical strategy and 12-month direction for AI-assisted self-service support, improving automated resolution quality and customer satisfaction while meeting Coinbase’s standards for safety, privacy, reliability, and cost. What you’ll do Lead a high-ownership engineering team building Help Center, social support, and agent knowledge experiences. Own end-to-end delivery of self-service discovery, conversational and agentic resolution, intelligent routing, escalation, and human handoff. Define architecture for secure, reliable, scalable systems spanning search, knowledge retrieval, chat orchestration, CRM, and ticketing integrations. Establish evaluation harnesses, quality metrics, feedback loops, and safeguards for accuracy, groundedness, privacy, and safety. Partner with Product, Design, CX Operations, Data, Compliance, Legal, Privacy, and Security on roadmaps, metrics, and execution. Evaluate build-versus-buy options and operationalize t
About the team The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope
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