Head of Engineering (AI Platform)

Join AiDASH, a rapidly growing company focused on satellite and AI-powered utility products. As the Head of Engineering for the AI Platform, you will build and lead a new Data Inference AI Pipeline team, architect a multimodal data inference pipeline, establish strong engineering practices, and partner with various teams to shape the roadmap. You will have the opportunity to make a significant impact on the company's growth and success.

Definir la misión del equipo, el plan de personal y los estándares de contratación, y realizar las primeras contrataciones.

Responsibilities

• Arquitectar una tubería de inferencia de datos multimodal que escale con el crecimiento del cliente.
• Establecer prácticas de ingeniería sólidas desde el primer día, incluyendo revisión de código, pruebas, proceso de lanzamiento.
• 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

Requirements

• A track record of building a team or system from scratch, not just scaling an existing one
• Proven ability to improve delivery predictability and accelerate onboarding and go-live for enterprise customers
• 10+ years of overall software engineering experience, including 3-5+ years leading engineering teams (managing managers or senior ICs)
• Confidence owning technical decisions within a defined scope, while partnering with a VP on strategy and resourcing
• Strong background in cloud-native, multi-tenant SaaS architectures (AWS, Kubernetes, microservices)
• 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
• 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 managing global, distributed engineering teams across multiple time zones
• 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

Pay

USD 300,000 - 330,000