Head of Engineering, AI Platform

AiDASH • Palo Alto, CA

1d • Hybrid

About The Position

AiDASH is hiring a Head of Engineering, AI Platform, a newly created role on its engineering leadership team. The role will build the Data Inference AI Pipeline team from the ground up and own the pipeline powering AI products as the company’s customer base grows. The position has significant ownership over technical decisions, team design, hiring, and engineering practices. It reports to the VP of Engineering and is based in Palo Alto, California, with a hybrid schedule requiring two days per week in the office.

The Head of Engineering will define the team’s charter, headcount plan, and hiring bar; make the initial hires; and architect a multimodal data inference pipeline that scales while keeping per-inference compute and infrastructure costs efficient. The role will establish model training and human-in-the-loop feedback loops, introduce effective engineering practices, and hire, coach, and develop engineering managers and leads. The leader will partner with Product, Data Science, and Design on roadmap trade-offs, collaborate with the VP of Engineering on cross-organization architecture decisions, and keep leadership informed about progress, risks, and resourcing.

In the first six months, the team is expected to have its first core hires and a scalable architecture in place, operate with clear ownership and a steady delivery cadence, and have visible practices for code review, on-call, and releases. Leadership should also have a clear, reliable view of the team’s progress, risks, and resourcing needs.

Requirements

• At least 10 years of overall software engineering experience, including 3–5 or more years leading engineering teams, such as managing managers or senior individual contributors.
• A track record of building a team or system from scratch, rather than only scaling an existing one.
• Hands-on experience architecting data or machine-learning 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 have shipped to production for real customers.
• Strong background in cloud-native, multi-tenant SaaS architectures, including AWS, Kubernetes, and microservices.
• Proven ability to improve delivery predictability and accelerate enterprise customer onboarding and go-live.
• Ability to own 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, collaborative spirit, and passion for building teams that do their best work.
• Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field.

Nice To Haves

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

Responsibilities

• Build the Data Inference AI Pipeline team, define its charter, headcount plan, and hiring bar, and make the initial hires.
• Architect a multimodal data inference pipeline that scales with customer growth while maintaining efficient compute and infrastructure costs per inference.
• Build model-training and human-in-the-loop feedback loops to keep AI accurate and continuously improving.
• Establish engineering practices, including code review, testing, on-call, and release processes.
• Hire, coach, and develop engineering managers and leads, manage performance as needed, and foster 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-organization architecture decisions.
• Provide leadership with a clear, reliable view of progress, risks, and resourcing needs.

Benefits

• Medical, dental, and vision coverage: 100% coverage for employees and 80% for spouses and children.
• Health Reimbursement Account (HRA), 100% funded by AiDASH to cover medical deductibles.
• 401(k) plan; employees may begin contributing after two months of employment, with no company match currently offered.
• Parental leave: 16 weeks for primary caregivers and 4 weeks for secondary caregivers.
• Accrual of 20 vacation days per year, plus an additional flex holiday.
• Winter break from December 25 through January 1.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior