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Salary: USD 300,000 - 330,000 / annual
AiDASH is a fast-growing climate tech company transforming grid resilience through satellite-powered AI and analytics for electric utilities. The company serves 200+ customers and is backed by strong investor recognition (Forbes Best Startup Employers 4x, TIME Top GreenTech 3x, Deloitte Tech Fast 500). AiDASH is pending acquisition by Schneider Electric, which will accelerate its mission at scale.
You will join as Head of Engineering, AI Platform, reporting to the VP of Engineering. This is a newly created role with the rare opportunity to build both a team and system from scratch. You will establish the Data Inference AI Pipeline team, defining its charter, hiring bar, and initial headcount plan. You'll make the first several hires from both within AiDASH and external talent.
Key responsibilities include:
- Architecting a multimodal data inference pipeline that scales efficiently with customer growth while controlling compute and infrastructure costs per inference
- Building model training and human-in-the-loop (HITL) feedback loops to keep AI accurate and continuously improving
- Establishing strong engineering practices from day one: code review, testing, on-call rotations, and release processes
- Hiring, coaching, and developing engineering managers and leads; managing performance and building a high-ownership culture
- Partnering with Product, Data Science, and Design on roadmap trade-offs and sequencing
- Owning technical decisions within your team's scope and collaborating with VP of Engineering on cross-org architecture
- Providing leadership with clear, reliable visibility into progress, risks, and resourcing needs
Success in the first 6 months means: core team hired and onboarded, scalable architecture deployed, clear ownership and delivery cadence established, visible engineering practices in place, and leadership has reliable visibility into team status.
Location: Palo Alto, CA (hybrid, 2 days per week in office).
Requirements:
- 10+ years of overall software engineering experience
- 3–5+ years leading engineering teams (managing managers or senior individual contributors)
- Strong experience building and scaling data pipelines, ML inference systems, or similar infrastructure
- Demonstrated ability to hire, develop, and retain high-performing engineering teams
- Experience architecting systems for scale, cost efficiency, and reliability
- Comfort with ambiguity and ability to define team charter and practices from scratch
- Track record of shipping products and delivering results in fast-growing environments
