Summary
What you’ll impact
The senior engineer will join the organization’s CTO small team to own end-to-end development of the AI-driven retail platform, building mobile capture, cloud infrastructure, backend services, data pipelines, APIs, and customer-facing applications. The role involves productionizing computer-vision and machine-learning systems, designing scalable architectures for thousands of stores, and working directly with retailer teams on deployments while making pragmatic technical decisions.
Responsibilities
What you'll do
- Build across mobile capture, cloud infrastructure, backend services, data pipelines, APIs, and customer-facing applications
- Productionize computer vision, machine-learning, and 3D reconstruction systems
- Design systems that can process data reliably across tens of thousands of retail locations
- Improve accuracy, latency, processing cost, observability, and fault tolerance
- Translate problems observed in stores into technical requirements and production software
- Work directly with retailer technology and operations teams on deployments and integrations
- Use AI coding tools and agents throughout the development process
- Make pragmatic decisions about architecture, technical debt, and when to build or integrate
- Help hire additional engineers as the company grows
Requirements
What you’ll bring
- You may have been a technical cofounder, founding engineer, or senior technical leader at an early-stage company.
- You should be comfortable operating without separate product, architecture, infrastructure, and engineering organizations around you.
- Built and operated a production product from zero to one
- Strong software engineering and system-design fundamentals
- Technical depth in multiple areas of the stack
- Experience owning architecture and production reliability
- The ability to work directly with customers and turn incomplete requirements into working software
- Experience making technical tradeoffs under real time, cost, and resource constraints
- A current, practical understanding of AI-assisted software development
- A preference for building over managing
- Computer vision, image processing, or 3D reconstruction
- Production machine-learning systems
- Android or mobile development
- Distributed data pipelines and real-time processing
- Enterprise SaaS, APIs, security, and integrations
- Software that interacts with physical environments
- Early-stage startup engineering