Internal Audit Lead in India

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 Exa team and lead the charge in redefining enterprise storage by unifying block, file, and object protocols across hybrid-cloud environments. You will combine deep technical expertise in distributed systems with hands-on people leadership to guide architectural decisions and mentor high-impact engineers. This is a unique opportunity to build new engineering teams from the ground up and drive industry-leading innovation alongside Product and Architecture partners. Your work will directly impact how customers consume, scale, and operate mission-critical storage infrastructure. WHAT YOU'LL DO Drive End-to-End System Architecture: Lead the architectural evolution and end-to-end delivery of high-performance, resilient storage systems from initial design concepts to high-quality shipped products. Optimize for Modern Data Workloads: Design and implement robust algorithms and concurrent platform solutions engineered for modern data pipelines, AI infrastructure, distributed computing, and enterprise analytics. Resolve Complex System Engineering Challenges: Apply deep root-cause analysis and system-level insight to solve multi-threaded, high-concurrency performance and reliability issues across Linux platform internals. Cross-Functional Ownership & Leadership: Collaborate across product management, validation, and support teams to align technical roadmaps, establish architectural standards, and drive ent

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About Ray Data Team: Ray Data is Python-native data processing engine that is a one stop shop for all AI data processing needs. Ray Data provides performant, first-class integration with cutting edge AI frameworks using both multi-modal and structured data. The Ray Data team currently develops and maintains Ray Data . We are a team of engineers passionate about building a Data processing engine which is a one-stop shop for all of your ML/AI needs. We are looking for exceptional engineers to build, optimize, and scale Ray for modern and increasingly complex AI workloads. As part of this role, you will: Improve the performance of Ray Data and multi-modal batch inference use cases. Ensure efficient scaling across different stages of the Data pipeline in a heterogeneous environment. Building data loading solutions for production training workloads. Focus on stability and fault tolerance at high scale Working with customers and new age AI native companies in scaling their AI workloads. We'd love to hear from you if have: At least 3-4 years of relevant work experience Solid background in building scalable and fault-tolerant distributed systems Experience with data processing, database internals. Passionate about large

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta Verify Team The Okta MacOS platform team is responsible for building Okta's MacOS Apps and SDKs. The Okta Verify app allows you to securely access your apps via 2-step verification, ensuring that you, and only you, can access your app accounts. It integrates with MacOS system features by communicating with our backend to and grant proper application access. Position Overview As a Senior SET, you will take end-to-end ownership of the test strategy, execution, and quality assurance for the Okta Verify macOS app, filling a critical gap as our existing framework scales to support advanced Apple feature sets. You will work closely with local engineers and cross-functional US-based mentors to design, build, and optimize scalable automation frameworks that completely replace manual testing validation for critical macOS authentication components. This role requires in-depth understanding of macOS system internals, native app archit

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 . We are seeking Capacity Planning Lead to join Coinbase's Consumer (CX) Workforce Management team. This role is central to translating volume trends, staffing assumptions, and business inputs into actionable short- and medium-range capacity plans that help our consumer support operation meet customer demand efficiently and cost-effectively. The ideal candidate brings deep WFM domain expertise, strong analytical fundamentals, and the ability to operate with ownership and precision in a fast-moving, AI-informed planning environment. You'll work at the intersection of forecasting, operations, and cross-functional stakeholder collaboration to ensure CX is always staffed to deliver a high-quality customer experience. What you’ll do: Own forecasts and short-range capacity plans across multiple consumer support queues and markets, translating volume, AHT, and shrinkage trends into staffing requirements and coverage plans Use hybrid human–AI tooling to build and maintain capacity models that reflect the growing complexity of our support channels and workforce structure Create multi-scenario staffing plans that model trade-offs between Customer Experience/Service Levels, Employee Experience, Operational Flexibility, and Cost Effectiveness Partner with vendor management and BPO partners to ensure staffing targets and contractual SLAs are met at the interval level C

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning

About the Role Support Operations is one of our core operations teams, responsible for making sure that when things go wrong, there's always someone there to make it right. The team designs, manages, and operates a large and growing global network of support centers, with the goal of delivering a world-class customer experience every time. We're looking for an experienced Workforce Planner to help develop and scale our support lines of business. This role is central to planning monthly, daily, and hourly staffing levels, and to keeping hiring plans current so we consistently deliver best-in-class service. You'll play a key part in improving forecast accuracy, reporting, and how we plan around floor staff utilization and efficiency — for a 24/7/365 organization, wherever it operates. You're excited about this opportunity because you will… Capacity planning Build and maintain support capacity plan models at the monthly, weekly, and interval level, using a quantitative model to determine the staff required to service forecasted volumes Match staffing supply to required staff to ensure efficient service level attainment, and make hiring, ramp, and staff-reduction recommendations Keep capacity plans and assumptions accurate, current, and aligned to source-of-truth headcount data, auditing regularly for accuracy Ensure alignment from the smallest site/team level of detail up through the broader org-wide capacity plan Maintain documentation of planning methodology, assumptions, and processes, and continually improve the planning tools, models, and templates themselves Forecasting & scenario planning Forecast incoming contact volume using historical and benchmark data, tracking deviations between forecast and actuals on a regular cadence Build, update, and present "what-if" scenarios to evaluate potential changes and support upcoming initiatives, as well as annual, half-year, and quarterly planning scenarios for long-range and financial planning Build and validate capac