About Granica Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information is transformed into usable intelligence. We’re built to streamline cloud infrastructure, reduce storage and compute costs, and accelerate data pipelines, therefore helping companies turn massive raw datasets into intelligent, usable fuel for AI. In short: we build better data for better AI . Smarter Infrastructure for the AI Era: We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3-based data lakes, enabling: 60%+ reduction in storage costs and up to 60% lower compute spend 3x faster data processing 20% platform efficiency gains Trusted by Industry Leaders Enterprise leaders globally already rely on Granica to cut costs, boost performance, and unlock more value from their existing data platforms. A Deep Tech Approach to AI We’re unlocking the layers beneath platforms like Snowflake and Databricks, making them faster, cheaper, and more AI-native. We combine advanced research with practical productization, powered by a dual-track strategy: Research: Led by Chief Scientist Andrea Montanari (Stanford Professor), we publish 1–2 top-tier papers per quarter. Product: Actively processing 100+ PBs today and targeting Exabyte scale by Q4 2025. Backed by the Best We’ve raised $60M+ from NEA, Bain Capital, A Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our Mission To convert entropy into intelligence, so every builder—human or AI—can make the impossible real. We’re building the default data substrate for AI, and a generational company built to endure beyond any single product cycle. Job Summary We are looking for a SDET (QA Automation Engineer) with hands-on experience in backend testing using Python , and working knowledge of Kubernetes , Apache Spark , and data lake architectures . In this role, you’ll collaborate with engineers across product and platform teams to ensure the quality of services powering our data-driven AI infrastructure. What You’ll Do 🧪Test Automation Design, develop, and maintain automated test scripts using industry-standard tools and frameworks Create and execute comprehensive test plans for APIs and big data applications Implement automated regression, functional, integration, and performance testing Develop and maintain test data management strategies Create reusable test components and maintain test automation frameworks 🗳️Quality Assurance Perform manual testing when required, including exploratory and usability testing Identify, document, and track software defects using bug tracking tools Collaborate with developers to reproduce and resolve issues Conduct root cause analysis for test failures and production issues Ensure compliance with quality standards and testing methodologies ♻️Process Improvement Integrate automated tests into CI/CD pipelines Provide testing estimates and ensure timely delivery of testing milestones Continuously evaluate and implement new testing tools and methodologies ✅ What We’re Looking For 3–6 years of experience in backend test automation with a strong focus on Python . Experience working in distributed systems , data engineering, or infrastructure-heavy environments. Familiarity with Apache Spark and related big data technologies. Hands-on experience with Kubernetes for container orchestration and test environment setup. Solid understanding of data lakes , including experience with formats (Parquet, ORC), storage layers, or lakehouse platforms. Experience with REST API testing , data validation, and large-scale test data management. Comfortable with tools like Pytest , Postman , Git , Jenkins , or similar CI/CD tools. Strong debugging and problem-solving skills in cloud-native environments. ✨ Nice-to-Haves Background in data infrastructure, machine learning pipelines, or systems programming Familiarity with distributed systems concepts (e.g., compression, storage tiering, streaming data) Experience working in a startup or fast-paced technical environment Experience with Kubernetes, Terraform, or infrastructure as code tools Comfort with performance tuning, benchmarking, and systems observability Why Granica? 💛 Work hands-on with petabyte-scale datasets , design performant systems and compression algorithms that matter Partner with elite engineers from companies like Google, Tesla, and Palantir on complex issues Tackle meaningful problems that push the boundaries of what’s possible in data infrastructure and AI Outcome-driven culture : Low ego, high trust, customer-obsessed. We scaled to multimillion-dollar ARR without a dedicated sales team—just product pull and ROI. Generous benefits : Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage Backed by top-tier VCs with strong runway and bold ambitions. Benefits: Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences Granica celebrates diversity and is committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
About Granica Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information is transformed into usable intelligence. We’re built to streamline cloud infrastructure, reduce storage and compute costs, and accelerate data pipelines, therefore helping companies turn massive raw datasets into intelligent, usable fuel for AI. In short: we build better data for better AI . Smarter Infrastructure for the AI Era: We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3-based data lakes, enabling: 60%+ reduction in storage costs and up to 60% lower compute spend 3x faster data processing 20% platform efficiency gains Trusted by Industry Leaders Enterprise leaders globally already rely on Granica to cut costs, boost performance, and unlock more value from their existing data platforms. A Deep Tech Approach to AI We’re unlocking the layers beneath platforms like Snowflake and Databricks, making them faster, cheaper, and more AI-native. We combine advanced research with practical productization, powered by a dual-track strategy: Research: Led by Chief Scientist Andrea Montanari (Stanford Professor), we publish 1–2 top-tier papers per quarter. Product: Actively processing 100+ PBs today and targeting Exabyte scale by Q4 2025. Backed by the Best We’ve raised $60M+ from NEA, Bain Capital, A Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our Mission To convert entropy into intelligence, so every builder—human or AI—can make the impossible real. We’re building the default data substrate for AI, and a generational company built to endure beyond any single product cycle. Job Summary We are looking for a SDET (QA Automation Engineer) with hands-on experience in backend testing using Python , and working knowledge of Kubernetes , Apache Spark , and data lake architectures . In this role, you’ll collaborate with engineers across product and platform teams to ensure the quality of services powering our data-driven AI infrastructure. What You’ll Do Test Automation Design, develop, and maintain automated test scripts using industry-standard tools and frameworks Create and execute comprehensive test plans for APIs and big data applications Implement automated regression, functional, integration, and performance testing Develop and maintain test data management strategies Create reusable test components and maintain test automation frameworks Quality Assurance Perform manual testing when required, including exploratory and usability testing Identify, document, and track software defects using bug tracking tools Collaborate with developers to reproduce and resolve issues Conduct root cause analysis for test failures and production issues Ensure compliance with quality standards and testing methodologies Process Improvement Integrate automated tests into CI/CD pipelines Provide testing estimates and ensure timely delivery of testing milestones Continuously evaluate and implement new testing tools and methodologies What We’re Looking For 6–10 years of experience in backend test automation with a strong focus on Python . Experience working in distributed systems , data engineering, or infrastructure-heavy environments. Familiarity with Apache Spark and related big data technologies. Hands-on experience with Kubernetes for container orchestration and test environment setup. Solid understanding of data lakes , including experience with formats (Parquet, ORC), storage layers, or lakehouse platforms. Experience with REST API testing , data validation, and large-scale test data management. Comfortable with tools like Pytest , Postman , Git , Jenkins , or similar CI/CD tools. Strong debugging and problem-solving skills in cloud-native environments. Nice-to-Haves Background in data infrastructure, machine learning pipelines, or systems programming Familiarity with distributed systems concepts (e.g., compression, storage tiering, streaming data) Experience working in a startup or fast-paced technical environment Experience with Kubernetes, Terraform, or infrastructure as code tools Comfort with performance tuning, benchmarking, and systems observability Why Granica? Work hands-on with petabyte-scale datasets , design performant systems and compression algorithms that matter Partner with elite engineers from companies like Google, Tesla, and Palantir on complex issues Tackle meaningful problems that push the boundaries of what’s possible in data infrastructure and AI Outcome-driven culture : Low ego, high trust, customer-obsessed. We scaled to multimillion-dollar ARR without a dedicated sales team—just product pull and ROI. Generous benefits : Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage Backed by top-tier VCs with strong runway and bold ambitions. Benefits: Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences Granica celebrates diversity and is committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale. We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains. Why It Matters Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills. Who We Are World renowned researchers in compression, information theory, and data systems Elite engineers from Google, Pure Storage, Cohesity and top cloud teams Enterprise sellers who turn ROI into seven‑figure wins. Powered by World-Class Investors & Customers $65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders Our Mission: We’re building the default data substrate for AI, and a generational company built to endure. About Granica Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information is transformed into usable intelligence. We’re built to streamline cloud infrastructure, reduce storage and compute costs, and accelerate data pipelines, therefore helping companies turn massive raw datasets into intelligent, usable fuel for AI. In short: we build better data for better AI . Smarter Infrastructure For The AI Era We make data efficient, safe, and ready for scale—think smarter, more foundational infrastructure for the AI era. Our technology integrates directly with modern data stacks like Snowflake, Databricks, and S3-based data lakes, enabling: 60%+ reduction in storage costs and up to 60% lower compute spend 3x faster data processing 20% platform efficiency gains Trusted by Industry Leaders Enterprise leaders globally already rely on Granica to cut costs, boost performance, and unlock more value from their existing data platforms. A Deep Tech Approach to AI We’re Unlocking The Layers Beneath Platforms Like Snowflake And Databricks, Making Them Faster, Cheaper, And More AI-native. We Combine Advanced Research With Practical Productization, Powered By a Dual-track Strategy Research: Led by Chief Scientist Andrea Montanari (Stanford Professor), we publish 1–2 top-tier papers per quarter. Product: Actively processing 100+ PBs today and targeting Exabyte scale by Q4 2025. Backed by the Best We’ve raised $60M+ from NEA, Bain Capital, A Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our Mission To convert entropy into intelligence, so every builder—human or AI—can make the impossible real. We’re building the default data substrate for AI, and a generational company built to endure beyond any single product cycle. Job Summary We are looking for a SDET (QA Automation Engineer) with hands-on experience in backend testing using Python , and working knowledge of Kubernetes , Apache Spark , and data lake architectures . In this role, you’ll collaborate with engineers across product and platform teams to ensure the quality of services powering our data-driven AI infrastructure. What You’ll Do 🧪Test Automation Design, develop, and maintain automated test scripts using industry-standard tools and frameworks Create and execute comprehensive test plans for APIs and big data applications Implement automated regression, functional, integration, and performance testing Develop and maintain test data management strategies Create reusable test components and maintain test automation frameworks 🗳️Quality Assurance Perform manual testing when required, including exploratory and usability testing Identify, document, and track software defects using bug tracking tools Collaborate with developers to reproduce and resolve issues Conduct root cause analysis for test failures and production issues Ensure compliance with quality standards and testing methodologies ♻️Process Improvement Integrate automated tests into CI/CD pipelines Provide testing estimates and ensure timely delivery of testing milestones Continuously evaluate and implement new testing tools and methodologies ✅ What We’re Looking For 7-10 years of experience in backend test automation with a strong focus on Python. Experience working in distributed systems, data engineering, or infrastructure-heavy environments. Familiarity with Apache Spark and related big data technologies. Hands-on experience with Kubernetes for container orchestration and test environment setup. Solid understanding of data lakes, including experience with formats (Parquet, ORC), storage layers, or lakehouse platforms. Experience with REST API testing, data validation, and large-scale test data management. Comfortable with tools like Pytest, Postman, Git, Jenkins, or similar CI/CD tools. Strong debugging and problem-solving skills in cloud-native environments. ✨ Nice-to-Haves Background in data infrastructure, machine learning pipelines, or systems programming Familiarity with distributed systems concepts (e.g., compression, storage tiering, streaming data) Experience working in a startup or fast-paced technical environment Experience with Kubernetes, Terraform, or infrastructure as code tools Comfort with performance tuning, benchmarking, and systems observability Why Granica? 💛 Work hands-on with petabyte-scale datasets, design performant systems and compression algorithms that matter Partner with elite engineers from companies like Google, Tesla, and Palantir on complex issues Tackle meaningful problems that push the boundaries of what’s possible in data infrastructure and AI Outcome-driven culture: Low ego, high trust, customer-obsessed. We scaled to multimillion-dollar ARR without a dedicated sales team—just product pull and ROI. Generous benefits: Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage Backed by top-tier VCs with strong runway and bold ambitions. Benefits Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences Granica celebrates diversity and is committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale. We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains. Why It Matters Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills. Who We Are World renowned researchers in compression, information theory, and data systems Elite engineers from Google, Pure Storage, Cohesity and top cloud teams Enterprise sellers who turn ROI into seven‑figure wins. Powered by World-Class Investors & Customers $65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders Our Mission: We’re building the default data substrate for AI, and a generational company built to endure. 🏄What You’ll Do Partner closely with customers to understand their technical environment, data challenges, and integration needs. Design and implement robust, scalable data pipelines from scratch using PySpark and Python, often in mission-critical environments. Configure and integrate modern data lakehouse and warehouse technologies including Apache Iceberg, Apache Hive, Delta Lake, Snowflake, and Databricks. Act as a trusted technical advisor—guiding customers through solution architecture, deployment, and troubleshooting. Contribute to internal tooling and automation to improve deployment velocity and system reliability. Collaborate with Granica’s engineering and product teams to influence roadmap decisions based on real-world customer use cases. Be an ambassador of the Granica product, both internally and externally. 💻Must-Have Qualifications What We're Looking For 5–10 years of hands-on experience in software engineering, data engineering, or infrastructure roles. Strong proficiency in Python and PySpark, with the ability to write clean, efficient, and scalable code. Proven experience building data pipelines from scratch, including ingestion, transformation, and optimization. Deep understanding and hands-on experience with: Apache Iceberg Apache Hive Apache Delta Lake Snowflake Databricks Experience working with large-scale data systems and distributed computing architectures. Ability to thrive in fast-paced, ambiguous environments typical of early-stage startups. Excellent problem-solving, communication, and customer-facing skills. ✨Nice-to-Haves Experience with Kubernetes, Terraform, or cloud-native infrastructure (AWS/GCP/Azure). Familiarity with security and privacy best practices in data processing pipelines. Prior experience in customer-facing technical roles (solutions engineer, customer engineer, etc.) is a strong plus. Why Granica? 💛 Work hands-on with petabyte-scale datasets, design performant systems and compression algorithms that matter Tackle meaningful problems that push the boundaries of what’s possible in data infrastructure and AI Work with top-tier engineering talent from companies like Google, Tesla, and Palantir and bleeding-edge data technologies. Own and lead critical projects with high visibility and impact. Flexible remote work culture with a globally distributed team. Outcome-driven culture: Low ego, high trust, customer-obsessed. We scaled to multimillion-dollar ARR without a dedicated sales team—just product pull and ROI. Generous benefits: Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage Backed by top-tier VCs with strong runway and bold ambitions. Benefits Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences Granica celebrates diversity and is committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale. We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains. Why It Matters Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills. Who We Are World renowned researchers in compression, information theory, and data systems Elite engineers from Google, Pure Storage, Cohesity and top cloud teams Enterprise sellers who turn ROI into seven‑figure wins. Powered by World-Class Investors & Customers $65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders Our Mission: We’re building the default data substrate for AI, and a generational company built to endure. What You’ll Do Infrastructure Design and Development: Design, build, and test the cloud-based infrastructure that supports Granica. AI's products, ensuring scalability, reliability, and performance. CI/CD Pipeline Management: Build and maintain robust CI/CD pipelines and related tooling in line with DevOps best practices to accelerate development velocity and improve product quality. Kubernetes Operations: Manage deployments to multiple production Kubernetes clusters, ensuring high availability and seamless operation while handling scaling challenges. End-to-End Testing: Contribute to and maintain our E2E testing framework, ensuring quality assurance across the platform. Cross-Team Collaboration: Participate in design discussions and code reviews, collaborating across teams to ensure best practices in infrastructure, cloud architecture, and development processes. Documentation and Knowledge Sharing: Write technical documentation to share solutions, capture tribal knowledge, and communicate complex issues and novel solutions. Project Leadership: Lead and drive projects from conception through to implementation, demonstrating initiative and leadership in an early-stage company environment. WHY JOIN GRANICA If you’ve helped build the modern data stack at a large company—Databricks, Snowflake, Confluent, or similar—you already know how critical lakehouse infrastructure is to AI and analytics at scale. At Granica, you’ll take that knowledge and apply it where it matters most…at the most fundamental layer in the data ecosystem. Own the product, not just the feature. At Granica, you won’t be optimizing edge cases or maintaining legacy systems. You’ll architect and build foundational components that define how enterprises manage and optimize data for AI. Move faster, go deeper. No multi-month review cycles or layers of abstraction—just high-agency engineering work where great ideas ship weekly. You’ll work directly with the founding team, engage closely with design partners, and see your impact hit production fast. Work on hard, meaningful problems. From transaction layer design in Delta and Iceberg, to petabyte-scale compaction and schema evolution, to adaptive indexing and cost-aware query planning—this is deep systems engineering at scale. Join a team of expert builders. Our engineers have designed the core internals of cloud-scale data systems, and we maintain a culture of peer-driven learning, hands-on prototyping, and technical storytelling. Core Differentiation: We’re focused on unlocking a deeper layer of AI infrastructure. By optimizing the way data is stored, processed, and retrieved, we make platforms like Snowflake and Databricks faster, more cost-efficient, and more AI-native. Our work sits at the most fundamental layer of the AI stack: where raw data becomes usable intelligence. Be part of something early—without the chaos. Granica has already secured $65M+ from NEA, Bain Capital Ventures, A* Capital, and legendary operators from Okta, Tesla, and Databricks. Grow with the company. You’ll have the chance to grow into a technical leadership role, mentor future hires, and shape both the engineering culture and product direction as we scale. Benefits Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences Help build the foundational infrastructure for the AI era Granica is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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. 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 Global Metadata Substrate. Help design and implement the metadata substrate that supports time-travel, schema evolution, and atomic consistency across massive tabular datasets. Adaptive Engines. Build components that reorganize data autonomously, learning from access patterns and workloads to maintain efficiency with minimal manual tuning. Intelligent Data Layouts. Develop and refine bit-level encodings, compression, and layout strategies to extract maximum signal per byte read. Autonomous Compute Pipelines. Contribute to distributed compute systems that scale predictively and adapt to dynamic load. Research to Production. Translate new algorithms in compression and representation from research into production-grade implementations. Latency as Intelligence. Design and optimize data paths to minimize time between question and insight, enabling faster learning for both models and humans. What You Bring Foundational understanding of distributed systems: partitioning, replication, and fault tolerance. Experience or curiosity with columnar formats such as Parquet or ORC and low-level data encoding. Familiarity with metadata-driven architectures or data query planning. Exposure to or hands-on use of Spark, Flink, or similar distributed engines on cloud storage. Proficiency in Java, Rust, Go, or C++ and commitment to clean, reliable code. Curiosity about how compression, entropy, and representation shape system efficiency and learning. A builder’s mindset—eager to learn, improve, and deliver features end-to-end with growing autonomy. Bonus Familiarity with Iceberg, Delta Lake, or Hudi. Contributions to open-source projects or research in compression, indexing, or distributed systems. Interest in how data representation influences AI training dynamics and reasoning efficiency. 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 Join us to build the foundational data systems that power the future of enterprise AI. At Granica, you will shape the fundamental infrastructure that makes intelligence itself efficient, structured, and enduring.