Product Manager — Research, Structured AI & Research Systems

Granica•San Francisco, CA

7d•$160,000 - $250,000•Onsite

About The Position

Granica is an AI research and infrastructure company building reliable and steerable representations for enterprise structured data. Granica’s Research team is advancing foundational work in: Tabular data learning and large tabular models Structured and relational representation learning Compression-aware and efficiency-driven AI Hybrid symbolic, relational, and neural systems The intersection of information theory, learning theory, and large-scale systems These efforts are tightly coupled with real production systems operating over petabytes of enterprise data. The mission of the Research Product Manager is to ensure this work moves forward coherently, efficiently, and at scale—connecting people, ideas, compute, and systems so that breakthrough research becomes durable capability. Granica is building foundational technology with a long horizon. The research happening here—particularly in structured and tabular AI—is aimed at reshaping how intelligence is built and applied across the global economy. As a Research Product Manager, you will: Enable breakthrough research to happen faster and land harder. Help define how frontier ideas become real systems. Play a central role in shaping the execution engine behind a generational research agenda. This role has real ownership, real influence, and a deep connection to the core of the company. Fundamental Research Meets Real Systems Work where theory, data, and large-scale engineering meet—and where research is expected to ship. Structured AI, Not Just Bigger Models Help advance a different path for AI: one grounded in structure, efficiency, and data-centric intelligence. High-Trust, High-Ownership Environment Minimal bureaucracy, deep technical work, and shared accountability for outcomes. Long-Term Horizon Backed by leading investors and built to last for decades, not product cycles. 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. 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!

Requirements

Background in computer science, AI, mathematics, physics, engineering, or a closely related field.
Experience in research program management, technical product management, or a similar role operating in highly technical environments.
Comfort engaging deeply with researchers and engineers on complex technical topics.
Strong written and verbal communication, especially around technical progress and trade-offs.

Nice To Haves

Experience working with or within a research lab (academic or industrial).
Familiarity with modern AI research workflows, including experimentation, evaluation, and large-scale training.
Ability to abstract at a high level while also diving into details when needed.
Master’s or PhD in a relevant technical field.
Publications or direct contributions to AI research (e.g., modeling, data, evals, systems, or related areas).
Experience supporting research in structured data, tabular models, or system-aware ML.
Demonstrated ability to learn new technical domains quickly.

Responsibilities

Drive Research Programs End-to-End
Own and coordinate complex, multi-threaded research initiatives spanning theory, data, infrastructure, and applied systems.
Ensure programs are well-scoped, milestones are clear, and progress is visible without slowing scientific velocity.
Translate Research into Execution
Turn technical ideas into concrete plans: timelines, dependencies, resourcing, and success criteria.
Help research teams move from exploration to validated results to system integration.
Operate at the Research–Systems Boundary
Work closely with Research Scientists, Applied AI engineers, and Systems teams to align experimental work with real-world constraints.
Support the path from novel algorithms and models—especially in structured and tabular domains—into production environments.
Resource & Compute Planning
Build and maintain compute and resource roadmaps across research programs.
Identify bottlenecks, trade-offs, and opportunities to improve utilization and iteration speed.
Cross-Functional Alignment
Collaborate across research, infrastructure, product engineering, legal, and business teams as needed.
Ramp quickly into new technical domains and help teams stay aligned as priorities evolve.
Communication & Synthesis
Synthesize progress across diverse technical efforts and communicate clearly to leadership and stakeholders.
Ensure the right information reaches the right people at the right time.