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 Lead and grow the team 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 Bachelor's or Master's in Computer Science, Engineering, or a related technical field Preferred Qualifications: Experience with geospatial data, satellite imagery, or remote-sensing pipelines A background in utilities, energy, or infrastructure Experience hiring and scaling a net-new engineering team in a high-growth (Series B/C) startup environment Open-source contributions, technical certifications, or published engineering writing What you'll love: Comprehensive Medical, Dental, and Vision Coverage: 100% coverage for employees and 80% for their spouses and children Health Reimbursement Account (HRA): 100% funded by AiDASH to cover medical deductibles 401(k) Plan: Begin contributing after two months of employment to prepare for your future. Currently, no company match is offered Parental Leave: Supportive parental leave with 16 weeks for primary caregivers and 4 weeks for secondary caregivers Generous Vacation Policy: Accrue 20 vacation days per year, plus enjoy an additional flex holiday to celebrate whatever feels most important to you Winter Break: From December 25th through January 1st, we give everyone time off to recharge and enjoy time with family and friends! We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work. We offer a competitive annual pay range of $300,000 to $350,000 for this full-time position, which includes a base salary and bonus based on performance. This range reflects the anticipated annual pay range (base + bonus) for new hires. We strive to ensure our compensation packages are equitable and aligned with industry standards. Your recruiter can share more about compensation during the hiring process. We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs. Read our Privacy Policy here: aidash.com

Requirements

Must-haves

Join us in Securing Tomorrow Together! The Role
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)
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
Lead and grow the team
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 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
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
Strong background in cloud-native, multi-tenant SaaS architectures (AWS, Kubernetes, microservices)

Nice-to-haves

Experience with geospatial data, satellite imagery, or remote-sensing pipelines
A background in utilities, energy, or infrastructure
Experience hiring and scaling a net-new engineering team in a high-growth (Series B/C) startup environment
Open-source contributions, technical certifications, or published engineering writing

Application prep

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Keywords to mirror

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Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave