Description
Principal Engineer
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Location: Redwood City, California (The Bay Area) - ideal for someone in Menlo Park, Redwood City, or San Francisco Bay Area. Home office with some travel to the office.
Reports To: Head of Product and Engineering
**Compensation: role comes with strong and competitive base salary, annual bonus and ESOP program (equity/shares) in a late stage Pre-IPO business! Total package is higher than the publicly posted target salary range**
About the company:
SaaS that helps connect physical locations, digital systems, and intelligent automation into one unified ecosystem. We build scalable, cloud-native systems that
integrate hardware, IoT, AI-driven applications, and enterprise SaaS to transform our clients business processes.
We are looking for a hands-on Principal Engineer who thrives at the intersection of system
architecture, hardware-software integration, and scalable SaaS platforms.
Role Overview
As a Principal Engineer, you will be a technical leader responsible for architecting, designing,
and scaling mission-critical systems across cloud, edge, and in-store environments. You will
work across hardware interfaces, distributed systems, AI-enabled applications, and multi-tenant
SaaS platforms.
This role requires deep technical expertise, strong ownership mindset, and the ability to operate
in a fast-paced startup environment.
Key Responsibilities
System Architecture & Technical Leadership
● Drive end-to-end system-level architecture across cloud, edge, and in-store
components.
● Define scalable, resilient, and secure architectures for multi-tenant SaaS platforms.
● Lead design reviews, technical strategy discussions, and long-term roadmap planning.
● Mentor senior engineers and influence engineering best practices.
Hardware–Software Integration
● Design and develop robust hardware-to-software interfaces.
● Integrate RFID, IoT, and edge devices with cloud platforms.
● Ensure real-time data ingestion, processing, and reliability at scale.
● Optimize performance across distributed systems and physical environments.
Cloud & SaaS Engineering
● Architect and build cloud-native applications on GCP (Google Cloud)
● Design and implement multi-tenancy models.
● Develop microservices-based architectures using:
○ Kubernetes
○ Docker / Containers
○ Message Queues (Kafka)
○ Redis
○ BigQuery
○ MongoDB
● Ensure high availability, observability, and scalability.
Application Development
● Develop backend systems using:
○ Java (Spring Boot)
○ Python (FastAPI or similar frameworks)
○ Node/NPM-based frameworks
● Contribute to API design, distributed system patterns, and event-driven architectures.
AI & Data Integration
● Work with AI/ML teams to integrate modeling outputs into production applications.
● Implement data pipelines and support analytics use cases.
● Apply AI-driven insights into real-world retail workflows.
Required Qualifications
● Bachelor’s degree in Computer Science, Electrical Engineering, or related field
OR equivalent demonstrated real-world engineering experience.
● 10+ years of experience in software engineering with deep system-level exposure.
● Proven expertise in:
○ Cloud-native SaaS systems (GCP preferred)
○ Multi-tenant architectures
○ Kubernetes & container orchestration
○ Microservices architecture
○ Kafka, Redis, MongoDB, BigQuery
○ Java (Spring Boot), Python frameworks, and Node/NPM ecosystem
● Experience designing scalable distributed systems.
● Strong understanding of hardware-software interaction patterns.
Preferred Qualifications
● Experience with RFID systems and IoT integration.
● Background in retail technology or operational systems.
● Exposure to AI/ML modeling and productionizing models.
● Experience building edge-to-cloud architectures.
Leadership & Cultural Fit
We are looking for someone who:
● Is a hands-on technical leader, not just a reviewer.
● Understands that “we are in the same boat” — collaborates deeply across teams.
● Is a self-starter who takes ownership without waiting for direction.
● Thrives in a fast-paced startup environment.
● Balances architectural thinking with pragmatic execution.
What Success Looks Like
● Scalable architecture that supports rapid customer growth.
● Reliable integration between store hardware and cloud systems.
● Clean, maintainable, high-performance codebases.
● Strong engineering culture with technical excellence as the bar.
