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Staff Infrastructure Software Engineer, Foundational Data Systems for AI — India (Remote) at Granica. Remote Location: India. Granica is an AI research and systems company building the infrastructure for a new kind of intelligence: one that is structured, efficient, and deeply integrated with data.. Our systems operate at . exabyte scale. , processing . petabytes of data each day. for some of the world’s most prominent enterprises in finance, technology, and industry. These systems are already making a measurable difference in how global organizations use data to deploy AI safely and efficiently.. We believe that the next generation of enterprise AI will not come from larger models but from . more efficient data systems. . By advancing the frontier of how data is represented, stored, and transformed, we aim to make large-scale intelligence creation sustainable and adaptive.. Our long-term vision is . Efficient Intelligence. : AI that learns using fewer resources, generalizes from less data, and reasons through structure rather than scale. To reach that, we are first building the . Foundational Data Systems. that make structured AI possible.. Snapshot. As a . Staff Infrastructure Software Engineer. , you will define and lead the architecture of Granica’s core infrastructure layer. This role owns . platform direction. , . reliability strategy. , and . developer infrastructure. across the company.. You will operate as a . technical leader. : setting standards, designing long-lived systems, and mentoring senior engineers while staying hands-on.. The Mission. AI today is limited not only by model design but by the inefficiency of the data that feeds it. At scale, each redundant byte, each poorly organized dataset, and each inefficient data path slows progress and compounds into enormous cost, latency, and energy waste.. Granica’s mission is to remove that inefficiency. We combine new research in . information theory. , . probabilistic modeling. , and . distributed systems. to design self-optimizing data infrastructure: systems that continuously improve how information is represented and used by AI.. This engineering team partners closely with the Granica Research group led by . Prof. Andrea Montanari. (Stanford), bridging advances in information theory and learning efficiency with large-scale distributed systems. Together, we share a conviction that the next leap in AI will come from breakthroughs in efficient systems, not just larger models.. What You’ll Build. Infrastructure & Platform Systems. Design and operate cloud infrastructure supporting petabyte–exabyte scale data systems. Own reliability, scalability, and observability of production environments. Kubernetes & Runtime Systems. Manage and evolve multiple production Kubernetes clusters. Design for high availability, fault tolerance, and predictable scaling. Debug issues across networking, storage, orchestration, and runtime layers. CI/CD & Developer Velocity. Build and maintain CI/CD pipelines that improve build speed, test reliability, and deployment safety. Reduce friction for systems, research, and product engineers shipping to production. End-to-End Testing & Reliability. Contribute to E2E testing frameworks and release confidence systems. Improve observability, alerting, and operational clarity. Cross-Team Collaboration. Partner with data systems engineers, applied AI teams, and product engineers. Participate in design reviews and infrastructure architecture discussions. What You’ll Bring. Core Requirements. Strong background in infrastructure, platform, or distributed systems engineering. Hands-on experience operating . production Kubernetes. environments. Experience with . CI/CD systems. and cloud infrastructure. Strong coding skills in . Go, Java, Python, or similar. Comfort debugging complex, cross-layer systems. Expectations. Own subsystems end-to-end with moderate ambiguity. Deliver reliable infrastructure improvements independently. Strong execution, growing architectural intuition. Bonus. Experience supporting data platforms or lakehouse systems. Familiarity with Spark, Trino, Iceberg, Delta, or large-scale analytics infra. Why This Role Matters. The infrastructure you build directly enables:. exabyte-scale data systems. fast research-to-production cycles. reliable enterprise AI workloads. This role has . real ownership. , . direct impact. , and a long technical horizon.. Why Granica. Fundamental Research Meets Enterprise Impact.. Work at the intersection of science and engineering, turning foundational research into deployed systems serving enterprise workloads at exabyte scale.. AI by Design.. Build the infrastructure that defines how efficiently the world can create and apply intelligence.. Real Ownership.. Design primitives that will underpin the next decade of AI infrastructure.. High-Trust Environment.. Deep technical work, minimal bureaucracy, shared mission.. Enduring Horizon.. Backed by NEA, Bain Capital, and various luminaries from tech and business. We are building a generational company for decades, not quarters or a product cycle.. Compensation & Benefits. Competitive salary, meaningful equity, and substantial bonus for top performers. Flexible time off plus comprehensive health coverage for you and your family. Support for research, publication, and deep technical exploration. At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring. . Join us to build the foundational data systems that power the future of enterprise AI!