Head of Engineering, AI Platform

Overview

Head of Engineering, AI Platform: a newly created engineering leadership role to build the Data Inference AI Pipeline team from the ground up and own the pipeline that powers AiDASH's AI products.

What you'll do

• Define the team's charter, headcount plan, and hiring bar, and make the first several hires from 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 the 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 the team's scope, and partner with the VP of Engineering on cross-org architecture decisions.
• Give leadership a clear, reliable view of progress, risks, and resourcing needs.

What you'll need

• 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.

Nice to have

• 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.

Details

• Location: Palo Alto, CA, hybrid with 2 days per week in the office.
• Full-time position.
• Reports to the VP of Engineering.
• Annual pay range of $300,000 to $330,000 (base plus performance-based bonus).