Engineering Manager - Autonomy Storage Infra

Applied Intuition•Sunnyvale, CA

1d•Onsite

About The Position

Applied Intuition is seeking an Engineering Manager to lead its Autonomy Storage Infra team within the Data & Compute organization. The manager will lead a data engineering team responsible for the full data lifecycle—from collection and ingestion through storage, querying, and retrieval—at hundreds of petabytes scale. The role partners with business units across Applied Intuition to define the storage infrastructure roadmap and support external products and internal tools across cloud, hybrid, and on-premises deployments. This cross-functional leadership role calls for technical credibility, people-management skills, and ownership. Engineering managers are expected to be hands-on leaders who contribute to technical direction. The role includes managing and mentoring engineers, setting architecture and reliability standards, driving technical decisions for high-volume autonomous vehicle and physical AI workloads, and recruiting and developing an inclusive, high-performing team. The company expects full-time employees to work primarily from an Applied Intuition office five days a week, while allowing occasional remote work and schedule flexibility. This expectation does not apply to contractor positions. Compensation for eligible roles includes base salary, equity, and benefits; the posting does not provide a salary range.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or equivalent.
At least 6 years of professional software engineering experience, including at least 2 years in an engineering management or tech lead role.
Hands-on experience with large-scale open-source data technologies such as Spark, Hudi/Iceberg, LanceDB, or dbt.
Track record of leading teams that build and operate high-scale distributed data systems.
Experience managing engineers across the full data lifecycle in a production environment.
Deep understanding of containerization, cloud-native architectures, and modern software development workflows.
Strong cross-functional communication skills and ability to influence technical direction at a senior level.

Nice To Haves

Experience with multi-cloud platforms (GCP, AWS, Azure) or multi-region data platforms, including data-residency requirements.
Experience with streaming and change data capture technologies such as Kafka, Pub/Sub, Flink, or Debezium, ideally at high scale.
Familiarity with data quality, data profiling, and data governance frameworks.
Experience building and operating observability or monitoring for data systems at scale.
Experience in high-growth environments where data infrastructure had to evolve rapidly with the business.
Prior exposure to automotive, defense, robotics, or other physical AI domains.

Responsibilities

Lead, grow, and mentor a team of data infrastructure engineers, fostering technical excellence, ownership, and collaboration.
Define and drive the technical roadmap for storage infrastructure, balancing near-term delivery with long-term scalability.
Own the architecture and reliability of systems supporting the full data lifecycle across cloud, hybrid, and on-premises environments and regions.
Drive engineering decisions for scalable data ingestion, indexing, storage, and retrieval for high-volume autonomous vehicle and physical AI workloads.
Establish and uphold engineering best practices, code quality standards, and operational excellence across the team.
Recruit engineering talent and build an inclusive, high-performing team.
Partner with business units across Applied Intuition to shape storage infrastructure and support external products and internal tooling.