Engineering Manager, Applied Intuition

• A Bachelor's degree in Computer Science, Software Engineering, or equivalent
• 6+ years of professional software engineering experience, with 2+ years in an engineering management or tech lead role
• Hands-on experience with large-scale open-source data technologies (Spark, Kafka, Hudi/Iceberg, Flyte, etc.)
• A strong 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 the ability to influence technical direction at a senior level
• Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles

Desirable

• We are looking for an Engineering Manager to lead our Data Platform team within the Data Engineering group. In this role, you will manage a world class data engineering team responsible for the full data lifecycle — from collection and ingestion to storage, querying, and retrieval — at hundreds of PBs scale
• You will partner closely with all business units across Applied Intuition to define the technical roadmap for our data platform and ensure we can reliably support both external products and internal tooling across cloud, hybrid, and on-prem deployments
• This is a highly cross-functional leadership role that requires deep technical credibility, strong people management skills, and a bias for ownership. At Applied Intuition, engineering managers are expected to be hands-on leaders who actively engage in technical direction, not just people management
• Lead, grow, and mentor a team of data infrastructure engineers, fostering a culture of technical excellence, ownership, and collaboration
• Define and drive the technical roadmap for data infrastructure, balancing short-term delivery with long-term scalability
• Partner with engineering, product, and business unit leaders to align data infrastructure investments with company priorities
• Own the architecture and reliability of systems that handle the full data lifecycle across all deployment environments (cloud, hybrid, on-prem) and regions
• Drive engineering decisions around scalable data ingestion, indexing, storage, and retrieval for high-volume autonomous vehicle and physical AI workloads
• Champion the adoption of modern open-source data technologies and maintain a disciplined approach to build-vs-buy decisions
• Establish and uphold engineering best practices, code quality standards, and operational excellence across the team
• Recruit top engineering talent and build an inclusive, high-performing team