Head of Engineering, AI Platform

aidashinc; Palo Alto (CA); Hybrid; USD 250,000 - 380,000; Full time

Job summary

AiDASH in Palo Alto is seeking a Head of Engineering, AI Platform to lead and build our Data Inference AI Pipeline team from the ground up. You will own architecture, hiring bar, and engineering practices as the company scales its AI products for a growing enterprise customer base.

Reporting to the VP of Engineering, you will shape technical decisions, coach managers and leads, and partner with Product, Data Science, and Design to align roadmap and execution.

Qualifications

• 10+ years of software engineering experience, including 3–5+ years leading engineering teams (managing managers or senior ICs)
• Track record of building a team or system from scratch
• Hands-on experience architecting data/ML pipelines at scale with throughput, latency, and cost trade-offs
• Experience building modern AI systems, shipped to production for real customers
• Strong background in cloud-native, multi-tenant SaaS architectures (AWS, Kubernetes, microservices)
• Proven ability to improve delivery predictability and accelerate onboarding and go-live for enterprise customers
• Confidence owning technical decisions within a defined scope while partnering with a VP on strategy
• Experience managing global, distributed engineering teams across multiple time zones
• High ownership mindset, low ego, collaborative culture

Skills

Software leadership

Data/ML pipelines

Cloud-native

AWS/Kubernetes

Architecture

Team-building

Global teams

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Kubernetes

Microservices

Job description

About AiDASH

AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire 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, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com.

The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024.

Join us in Securing Tomorrow Together!

The Role

AiDASH is scaling fast - o ur satellite and AI-powered utility products are set for aggressive customer growth over the next two years, and engineering is at the heart of making it happen. We're hiring a Head of Engineering, AI Platform to join our engineering leadership team in a newly created role. In this role, y ou'll build our new Data Inference AI Pipeline team from the ground up to support our rapidly growing customer base.

This is a rare opportunity to build both the team and the system from scratch: you'll shape the architecture, culture, and hiring bar of a new AI team from day one, and own the pipeline that powers our AI products as our customer base grows. In this role, you will report to the VP of Engineering and have real ownership over technical decisions, team design, and engineering practices.

Our pending acquisition by Schneider Electric will accelerate our mission as we bring our combined offering to our joint customer base, and the systems you build will power outcomes at an even greater scale.

Location

Palo Alto, CA (hybrid/2 days per week in the office)

How you'll make an impact:

• Build the Data Inference AI Pipeline team
• Define the team's charter, headcount plan, and hiring bar, and make the first several hires, bringing in talent from both within AiDASH and outside
• Architect a multimodal data inference pipeline that scales with customer growth while keeping compute and infrastructure cost per inference efficient
• Build the model training and human-in-the-loop (HITL) feedback loops that keep our AI accurate and continuously improving
• Establish strong engineering practices from day one, including code review, testing, on-call, and release process
• Hire, coach, and develop engineering managers and leads, and manage performance as needed, building 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 team's scope, and partner with the VP of Engineering on cross-org architecture decisions
• Give the leadership a clear, reliable view of progress, risks, and resourcing needs

What success looks like in your first 6 months:

• The Data Inference AI Pipeline team is staffed with its first core hires, from within AiDASH and outside, and running on an architecture that scales with growing data volume without a proportional rise in infrastructure cost
• The team has clear ownership, a steady delivery cadence, and visible engineering practices (code review, on-call, release process) in place
• Leadership has a clear, reliable read on the team's progress, risks, and resourcing needs

What we're looking for:

Minimum Qualifications

• 10+ years of overall software engineering experience, including 3-5+ years leading engineering teams (managing managers or senior ICs)
• A track record of building a team or system from scratch, not just scaling an existing one
• Hands-on experience architecting data/ML pipelines at scale, with a strong grasp of throughput, latency, and cost-efficiency trade-offs for inference workloads
• Experience building modern AI systems, including reasoning frameworks, agentic capabilities, retrieval-augmented generation (RAG), self-correction loops, and memory and state management, that shipped to production for real customers, not as research or internal proof-of-concept work
• Strong background in cloud-native, multi-tenant SaaS architectures (AWS, Kubernetes, microservices)
• Proven ability to improve delivery predictability and accelerate onboarding and go-live for enterprise customers
• Confidence owning technical decisions within a defined scope, while partnering with a VP on strategy and resourcing
• Experience managing global, distributed engineering teams across multiple time zones
• High ownership mindset, low ego, and a collaborative spirit, with a passion for building teams that do their best work
• Bach