Engineering Manager – Foundational Data Systems AI

Engineering Manager — Foundational Data Systems for AI

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

Team: Foundational Data Systems

We’re hiring an Engineering Manager (Hands-on TLM) 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 technical leadership position requiring regular participation in architecture reviews, system design, debugging complex distributed systems issues, and occasional coding.

You will help design and operate the core infrastructure behind Granica’s open-table data systems
, working with formats such as Apache Iceberg, Delta Lake, and Parquet
.

Deep experience with open table formats and their internals—including metadata layers, transaction commits, compaction, schema evolution, and table maintenance is strongly preferred.

The systems this team built 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, designing durable distributed systems, and operating infrastructure that must be correct and efficient at enterprise scale.

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 layers, and expensive execution paths translate directly into:

• higher infrastructure costs
• slower iteration cycles
• operational fragility

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 engineering team across multiple geographies
• Own hiring, onboarding, and career development in a high-bar engineering culture
• Create clarity and accountability across a large, senior organization operating in ambiguity

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

Remain deeply involved in architecture and system design decisions
.

Own the evolution of foundational systems including:

• Table maintenance and data layout optimization
• Metadata services and transaction management
• Schema evolution and versioning
• Distributed compute orchestration
• Reliability, observability, and operational tooling

These systems operate on petabyte-scale datasets and must meet strict requirements for correctness, durability, and efficiency.

• Translate strategy into execution through clear roadmaps and milestones
• Establish engineering standards for correctness, reliability, and cost efficiency
• Lead incident response, postmortems, and system improvements
• Operate infrastructure where correctness and durability are critical

• 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…