What are the responsibilities and job description for the Engineering Manager – Foundational Data Systems for AI [32995] position at Stealth Startup?
About us
The company 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.
Engineering Manager — Foundational Data Systems for AI
Location: Downtown Mountain View, CA (office-based, 5 days/week)
Team: Foundational Data Systems
About the Role
We’re hiring an Engineering Manager to lead our core team building company's Foundational Data Systems—the 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, owning systems across storage, metadata, compute, and infrastructure. This is a high-impact leadership role with real architectural influence and long-term ownership.
Data infrastructure is critical at the company. The systems your team builds directly determine the reliability, efficiency, and velocity of our research, product development, and enterprise deployments.
This role is ideal for a technically strong leader who enjoys building teams, shaping systems that last, and operating with high trust and autonomy.
The Mission
AI today is constrained not just by model design, but by the inefficiency of the data that feeds it. At scale, redundant bytes, poorly organized datasets, and inefficient data paths translate directly into higher cost, slower iteration, and wasted energy.
Company's mission is to remove that inefficiency at the foundation. We design self-optimizing data infrastructure—systems that continuously reorganize, compress, and maintain structured data so it can be learned from efficiently and reliably by AI systems.
This engineering team works closely with the company's Research group led by Prof. Andrea Montanari (Stanford), translating advances in information theory and learning efficiency into large-scale distributed systems. Together, we believe the next major advance in AI will come from better systems and better data, not simply larger models.
What You’ll Do
- Lead, mentor, and grow a team of senior engineers across multiple geographies
- Own hiring, onboarding, and career development in a high-bar engineering culture
- Set technical direction through design reviews, RFCs, and principled trade-offs
- Own the design and evolution of foundational systems spanning:
- Table maintenance and data layout
- Metadata, transactions, and schema evolution
- Distributed compute and orchestration
- Reliability, observability, and operational tooling
- Translate strategy into execution through roadmaps and milestones
- Establish and uphold reliability, latency, and operational standards
- Lead incident response, postmortems, and continuous system improvement
- Partner closely with Research, Applied AI, Product, and Infrastructure teams to move ideas from research into production
Skills and Qualifications
Minimum Qualifications
- 7 years of experience in backend, infrastructure, or distributed systems engineering
- 2 years leading engineering teams or large, multi-person technical initiatives
- Deep expertise in distributed compute frameworks (e.g., Spark, Trino, Presto) and columnar formats (Parquet, ORC)
- Experience building or operating data platforms, lakehouse systems, or large-scale analytics infrastructure
- Strong systems design instincts across distributed compute, storage, and data platforms
- Experience operating and scaling production systems with real reliability requirements
- Hands-on technical background; comfortable participating in deep technical discussions
Preferred Qualifications
- Experience with Iceberg, Delta Lake, or similar table formats
- Experience partnering closely with research or ML teams
- Track record of scaling teams in high-ambiguity, fast-moving environments
Logistics
- Location: Downtown Mountain View, CA
- Work model: Office-based, five days per week
- Team: Foundational Data Systems
- Leadership scope: ~15–20 engineers across the US, India, and Canada
Why us
- 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