Principal Platform Engineer (Edge + IoT + SaaS)

Description Principal Engineer d 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.

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