Engineering Manager – Foundational Data Systems for AI

Granica is an AI research and infrastructure company focused on reliable, steerable representations for enterprise data.

We earn trust through Crunch, a policy-driven health layer that keeps large tabular datasets efficient, reliable, and reversible. On this foundation, we’re building Large Tabular Models—systems that learn cross-column and relational structure to deliver trustworthy answers and automation with built-in provenance and governance.

Location: Downtown Mountain View, CA (office-based, 5 days/week)
Team: Foundational Data Systems

We’re hiring an Engineering Manager to lead Granica’s Foundational Data Systems—the core infrastructure layer that everything else depends on.

You’ll lead a globally distributed team of ~15–20 senior engineers across the US, India, and Canada, with direct ownership of long-lived systems spanning storage, metadata, and distributed compute. This is not a people-only management role. It is a hands-on leadership position with real architectural authority, responsible for building systems that must be correct, durable, and efficient at enterprise scale.

The systems this team builds determine whether Granica can translate cutting-edge research into reliable products and whether our customers can trust the data foundations their analytics and AI workloads depend on.

This role is ideal for a technically strong leader who enjoys building teams, shaping systems that last for a decade, and operating with high trust and ownership.

Modern AI and analytics systems are constrained less by models and more by the inefficiency and fragility of the data infrastructure beneath them. Redundant data layouts, brittle metadata, and expensive execution paths directly translate into higher cost, slower iteration, and operational risk.

Granica’s mission is to remove that inefficiency at the foundation.

We design self-optimizing data systems that continuously reorganize, compress, and maintain structured data so it remains efficient, reliable, and reversible as it evolves. These systems serve as the durable substrate for analytics, automation, and AI workloads—where correctness, provenance, and governance are non-negotiable.

This team works closely with Granica’s Research group led by Prof. Andrea Montanari (Stanford), translating advances in information theory and learning efficiency into production-grade distributed systems. We believe the next major step forward will come not from larger models, but from better systems and better data.

• Lead, mentor, and grow a senior team across multiple geographies

• Own hiring, onboarding, and career development in a high-bar engineering culture

• Create clarity and accountability across a large, senior org operating in ambiguity

• Set technical direction through design reviews, RFCs, and principled trade-offs

• Maintain close involvement in architecture and core system decisions

• Own the evolution of foundational systems including:

  • Table maintenance and data layout

  • Metadata, transactions, and schema evolution

  • Distributed compute and orchestration

  • Reliability, observability, and operational tooling

• Translate strategy into execution via clear roadmaps and milestones

• Establish and uphold standards for correctness, reliability, and cost efficiency

• Lead incident response, postmortems, and continuous system improvement

• Work closely with Research, Applied Systems, Product, and Infrastructure teams

• Help move ideas from theory to production while preserving system integrity

• Act as a technical and organizational bridge between research and engineering

• 7+ years of experience in backend, infrastructure, or distributed systems engineering

• 2+ years leading engineering teams or large, multi-person technical initiatives

• Strong systems design instincts across distributed compute, storage, and data platforms

• Experience building or operating data platforms, lakehouse systems, or large-scale analytics infrastructure

• Hands-on technical background; comfortable engaging in deep architectural discussions

• Track record of operating and scaling production systems with real reliability requirements

• Experience with table formats such as Iceberg, Delta Lake, or similar systems

• Familiarity with distributed compute frameworks (e.g., Spark, Trino, Presto)

• Experience partnering closely with research or ML-adjacent teams

• Success scaling teams in high-ambiguity, fast-moving environments

• Location: Downtown Mountain View, CA

• Work model: Office-based, five days per week

• Team size: ~15–20 engineers across the US, India, and Canada

• 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.

• 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!