Head of Engineering, AI Platform
Aidashinc · Palo Alto, California, United States
About this role
## About AiDASH AiDASH is leading the **PreventionFirst™** movement for electric utilities—transforming grid resilience with a platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by **SatelliteFirst™** Inspection & Monitoring, AiDASH delivers comprehensive visibility across the grid at the right frequency and budget, using the right data modality. More than **200 customers** trust AiDASH to keep the lights on, spend where it counts, and defend every decision. Learn more: https://www.aidash.com --- ## The Role — Head of Engineering, AI Platform AiDASH is scaling fast, and engineering is at the heart of aggressive customer growth over the next two years. We’re hiring a **Head of Engineering, AI Platform** to join our engineering leadership team in a newly created role. In this position, you’ll build our **Data Inference AI Pipeline** team from the ground up—shaping the architecture, culture, hiring bar, and owning the pipeline that powers our AI products as our customer base grows. You’ll report to the **VP of Engineering** and have real ownership over technical decisions, team design, and engineering practices. **Location:** Palo Alto, CA (**hybrid / 2 days per week in office**) --- ## How you’ll make an impact - **Build the Data Inference AI Pipeline team** - Define the team’s charter, headcount plan, and hiring bar; make the first hires - Architect a **multimodal data inference pipeline** that scales with customer growth while keeping compute/infrastructure cost per inference efficient - Build **model training** and **human-in-the-loop (HITL)** feedback loops to keep AI accurate and continuously improving - Establish strong engineering practices from day one (code review, testing, on-call, release process) - **Lead and grow the team** - Hire, coach, and develop engineering managers/leads; build a high-performing, high-ownership culture - Partner with Product, Data Science, and Design to shape roadmap trade-offs and sequencing - Own technical decisions within your scope; partner on cross-org architecture decisions - Provide leadership with a clear, reliable view of progress, risks, and resourcing needs --- ## Success in your first 6 months - The Data Inference AI Pipeline team is staffed with first core hires and running on an architecture that scales with data volume without proportional infrastructure cost increases - Clear ownership, steady delivery cadence, and visible engineering practices in place (code review, on-call, release process) - Leadership has a clear, reliable read on progress, risks, and resourcing needs --- *Note: The provided description appears truncated after “Minimum Qualifications.” If you share the rest, I can format the remaining sections too.*
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