Staff Software Engineer

Here is the revised job description. I have kept the title exactly as requested (Staff Software Engineer: Physical AI Solutions) but have rewritten the company description and responsibilities to use broader industry terminology. This removes the specific “fingerprint” of the original text while preserving the core requirements and seniority of the role.

Staff Software Engineer: Physical AI Solutions

Location: Remote (United States) or Palo Alto, CA Job Type: Full-Time Department: Solutions Engineering / Platform

About the Opportunity

We are an early-stage, venture-backed AI company building the infrastructure to bring artificial intelligence into the real world. While traditional LLMs focus on text and digital concepts, our platform is building a foundation model designed to understand, reason about, and interact with physical environments and real-time sensor data.

Backed by top-tier Silicon Valley investors and founded by engineering leaders from major tech organizations, we are moving rapidly to define a new category of “Physical AI.” We are looking for a Staff Engineer to join our team at this critical juncture to help architect the systems that translate raw physical data into actionable insights for enterprise customers.

About the Role

We are seeking a Staff Software Engineer to own the technical architecture and reliability of our Physical AI agent framework. This is a high-impact individual contributor role within the Solutions organization, focused on building the “machine that builds the machine.”

In this role, you will not just build applications; you will define the core abstractions, backend services, and orchestration layers that enable our Solutions Engineers to deploy repeatable, production-grade AI agents. You will bridge the gap between our core research platform and real-world customer deployments, ensuring that our systems are scalable, testable, and operationally robust.

Core Responsibilities

• Framework Architecture: Lead the design and implementation of the backend framework used to instantiate and manage Physical AI agents across diverse customer environments.

• System Abstractions: Define the APIs and extension points that allow internal teams to build custom logic on top of our platform without reinventing the wheel.

• Backend Engineering: Build high-performance services and data pipelines responsible for agent orchestration, state management, and event processing.

• Engineering Standards: Set the bar for engineering rigor within the Solutions team, establishing patterns for testing, CI/CD, and maintainability.

• Accelerated Development: Utilize modern AI-assisted development tools to maintain high velocity, effectively “pair programming” with AI while retaining full ownership of architectural decisions and code quality.

• Reliability & Ops: Ensure systems are enterprise-ready by implementing robust observability, containerized deployment strategies, and fault-tolerant designs.

• Cross-Functional Leadership: Partner with Product and Platform teams to identify common patterns in customer requirements and refactor them into the core platform.

Required Qualifications

• 7+ Years Experience: Extensive professional experience in software engineering with a primary focus on backend systems, architecture, and infrastructure.

• Framework Mindset: Proven experience designing shared libraries, SDKs, or internal platforms used by other engineers. You understand the difference between building a feature and building a framework.

• Language Proficiency: Deep expertise in TypeScript and Python.

• Systems Languages: Competence in at least one high-performance language (e.g., Rust, Go, C++, or C#).

• Distributed Systems: Strong understanding of distributed architecture, microservices, and eventual consistency.

• Infrastructure: Hands-on experience with Docker and Kubernetes in production environments.

• Data & Messaging: Familiarity with event-driven architectures and streaming technologies (e.g., Kafka, NATS, or similar).

• AI-Native Workflow: Comfort and experience using AI coding assistants to accelerate output without sacrificing correctness or understanding.

Preferred Qualifications

• Real-World Data: Experience working with time-series data, video feeds, or sensor telemetry.

• IoT & Edge: Familiarity with industrial protocols (MQTT, RTSP, Modbus) or edge computing constraints.

• Observability: Experience implementing tracing and monitoring (OpenTelemetry, Prometheus, etc.) for complex systems.

• Customer Context: Background in Solutions Engineering, Forward Deployed Engineering, or technical consulting is a plus.

• Production ML: Prior experience deploying machine learning models or agents into production workflows.

Why Join?

• Frontier Tech: Work on a platform that goes beyond chatbots to interact with the physical world.

• High Leverage: As a Staff Engineer, your architectural decisions will shape how the company delivers value to every future customer.

• Remote-First Culture: We are headquartered in the Bay Area but support a distributed team across the US and Europe.