Software Engineer: Physical AI Solutions

Staff Software Engineer:
Physical AI Solutions

Job type:
Full Time
· Department:
Solutions Engineering
· Work type:
Remote

Archetype AI is developing the world's first AI platform to bring AI into the real world. Formed by an exceptionally high-caliber team from Google, Archetype AI is building a foundation model for the physical world, a real-time multimodal LLM for real life, transforming real-world data into valuable insights and knowledge that people will be able to interact with naturally. It will help people in their real lives, not just online, because it understands the real-time physical environment and everything that happens in it.

Supported by deep tech venture funds in Silicon Valley, Archetype AI is currently pre-Series A, progressing rapidly to develop technology for their next stage. This presents a unique and once-in-a-lifetime opportunity to be part of an exciting AI team at the beginning of their journey, located in the heart of Silicon Valley.

Our team is headquartered in Palo Alto, California, with team members throughout the US and Europe.

We are actively growing, so if you are an exceptional candidate excited to work on the cutting edge of physical AI and don’t see a role that exactly fits you below you can contact us directly with your resume via jobsarchetypeaiio.

We are hiring a Staff Software Engineer responsible for the design, evolution, and reliability of our Physical AI systems and agent framework within the Solutions organization. This role defines the architecture and core abstractions for enterprise-grade Physical AI agents and the systems that support them.

This is a Staff-level individual contributor role with clear technical ownership. You will shape how agents and supporting systems are built, extended, tested, and operated, enabling internal teams to deliver repeatable, production-ready solutions to enterprise customers. While the role occasionally involves building reference integrations or supporting customer engagements, the primary focus is backend systems, framework design, and engineering rigor rather than UI-heavy application development.

The role reports into the Head of Solutions Engineering and works closely with Solutions Engineers, Product, and the Platform team to translate real-world requirements into durable, reusable systems.

Drive the architecture, design, and implementation of the Physical AI agent framework used across customer solutions.

Define and evolve core abstractions, APIs, and extension points that enable others to build agents and systems on top of the framework.

Design and implement backend services and data pipelines that support agent execution, orchestration, and data flow.

Ensure systems are built with enterprise readiness in mind, including reliability, testability, and operational robustness.

Establish engineering patterns and standards for backend systems within the Solutions organization.

Build reference integrations or lightweight applications when needed to validate capabilities or support customer engagements.

Partner with Solutions Engineers to convert customer-specific requirements into reusable framework features.

Use modern AI coding agents in a pair-programming model to accelerate development, while retaining ownership of architecture, code quality, and correctness.

Contribute to CI/CD workflows, containerized deployments, and operational tooling.

Produce clear documentation that enables adoption, extension, and long-term maintainability of the framework.

7+ years of professional software engineering experience with a strong backend and systems focus.

Demonstrated experience owning and evolving shared frameworks or core systems used by other engineers.

Strong proficiency in Type Script and Python.

Experience with at least one high-performance or systems-oriented language, such as Rust, C++, C#, Go, or similar.

Solid foundation in distributed systems, backend architecture, and data pipelines.

Experience building and operating long-running services or orchestration systems in production.

Familiarity with messaging or streaming systems such as Kafka or similar technologies.

Experience working in containerized environments using Docker and Kubernetes.

Strong engineering fundamentals, including code review discipline and experience using AI-assisted development tools without delegating ownership.

Clear written and asynchronous communication skills.

Experience with real-time, sensor-driven, or event-based systems, including industrial or video workloads.

Familiarity with IoT or industrial protocols such as MQTT, Modbus, or RTSP.

Experience with observability, instrumentation, and performance tuning in distributed systems.

Background in solutions engineering or consulting, with comfort engaging directly with customers when needed.

Exposure to applied AI or ML systems in production environments

Experience with machine learning and artificial…