Head of AI Platform Engineering

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

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.