Director of Engineering-- Data Infrastructure

Director of Engineering

• Data Infrastructure at DreamVu AI Director of Engineering
• Data Infrastructure at DreamVu AI in Camden, New Jersey Posted in about 2 hours ago.

Type:

full-time

Job Description:

About the Role DreamVu builds data infrastructure for Physical AI

• capturing, processing, and annotating real-world multimodal data used to train humanoid robots and embodied AI systems.

We're looking for a Director of Engineering to own the infrastructure that powers our data operations. This is a pure engineering leadership role focused on reliability, scalability, throughput, and cost efficiency. The ideal candidate has run large-scale cloud or data infrastructure in a demanding production environment

• and managed the cost of doing so
• and wants to apply that experience to one of the most consequential data problems in AI. What You Will Own The role spans three areas: Pipeline operations
• end-to-end ownership of the data pipeline, from raw sensor capture through pre-processing, automated pre-annotation, and human-in-the-loop annotation and QA. Full pipeline details are shared during the interview process. Cloud infrastructure and cost
• ownership of the cloud platform the pipeline runs on: provisioning, scaling, reliability, and the cost efficiency of it all. You'll treat spend as a first-class engineering metric
• right-sizing compute and storage, controlling unit economics as data volume grows, and keeping cost-per-hour-of-data on a downward trend. Systems integration and tooling
• hardening and stabilizing new pipeline components into production, plus the monitoring, alerting, QA frameworks, dataset management, workflow tooling, and operational documentation that support consistent delivery. Responsibilities Own pipeline reliability, throughput, and quality SLAs end-to-end Own cloud infrastructure spend
• forecast, monitor, and continuously optimize cost as data volume scales Build and lead the engineering and operations team as the pipeline grows Define and manage how new pipeline components become stable production systems Maintain a clear view of technical debt and a plan to address it Establish engineering practices
• code standards, review processes, incident response, documentation Translate data capture roadmaps into capacity plans and delivery schedules Maintain visibility into pipeline health and cost for the team and leadership Coordinate with capture operations ahead of new data collection campaigns What We're Looking For 8+ years in engineering, including 3+ years in a leadership role
• ideally in cloud services, data infrastructure, or large-scale platform engineering Track record running high-throughput, high-availability production systems on AWS, GCP, or Azure Demonstrated ownership of cloud cost
• you've managed infrastructure budgets and driven down unit economics at scale Strong operational instincts
• you define SLAs, instrument systems proactively, and treat instability as an engineering problem to be solved Solid Python fundamentals and comfort extending an existing codebase Experience building and managing small, high-ownership engineering teams under delivery pressure Strong planning and communication skills
• comfortable reporting status and cost clearly to the CTO Nice to have: experience with video or multimodal data at scale (depth, point clouds, sensor streams) Nice to have: experience with annotation platforms or human-in-the-loop tooling What Makes This Role Distinctive DreamVu's pipeline processes multimodal sensor streams at scale across a complex, multi-stage workflow. The challenges
• throughput, reliability, cost efficiency, and quality at volume
• are the same class of problems found in demanding cloud data platforms, but applied to a domain at the frontier of AI.

For an infrastructure leader who wants high ownership and meaningful scope, this is an unusually substantive opportunity. Location & Structure Based at our Philadelphia office, with regular coordination with our Hyderabad team. Reports to the CTO.