Backend Software Engineer: Streaming
About The Position
About Archetype AI 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. About the Role We’re looking for a highly motivated backend engineer with extensive experience in designing and developing performant, scalable, and resilient data streaming services. You’ll work closely with researchers, ML engineers, and product teams to bring cutting-edge AI capabilities into production—at scale, with reliability, and under real-world constraints. This is an opportunity to own key services across our real-time AI platform related to real-time data streaming, to optimize for latency and throughput, and contribute to some of the most advanced systems in production today.
Requirements
- 7+ years of professional software engineering experience, with a focus on real-time data streaming (e.g. video, audio, message streams).
- Deep understanding of data streaming protocols, including modern networking protocols (e.g. QUIC).
- Experience designing and optimizing custom streaming technologies for real-time data transfer.
- Ability to design APIs for real-time and near-real-time data streaming use cases.
- Experience building and operating production-grade systems at scale in cloud environments (e.g., Azure, AWS, GCP).
- Strong debugging, instrumentation, and observability skills across distributed systems.
- Demonstrated ownership of complex technical problems and ability to learn and adapt quickly.
Nice To Haves
- Proven track record of scaling systems through rapid growth and rebuilding or refactoring for new demands.
- Experience building systems that degrade gracefully under load: back pressure, rate limiting, circuit breaking, bulk heading, and queuing.
- Strong understanding of failure modes in distributed systems and mitigation techniques.
- Proven experience owning high-availability services (e.g., SLOs, incident response, on-call), including capacity planning and load testing.
- Proficiency in multiple programming languages (e.g., Rust, C++, Python).
- Experience designing internal tools or platforms to support developer productivity and experimentation.
- Strong product intuition, and ability to collaborate closely with cross-functional teams including research and design.
Responsibilities
- Architect, implement, and maintain real-time data streaming systems that support high-throughput, low-latency data services (e.g. sensor data edge-to-cloud streaming).
- Continuously optimize real-time streaming performance from client-to-cloud for a wide range of real-time sensor data types (e.g. video, time series, sensor logs, lidar, radar, audio).
- Build tooling and observability to monitor system health, identify bottlenecks, and proactively resolve instability.
- Introduce new techniques, architectures, and best practices to push the limits of scalability, efficiency, and reliability.
- Own problems end-to-end—from design to deployment—with a strong bias toward quality, automation, and continuous improvement.
- Balance rapid iteration on early-stage systems with long-term maintainability and architectural soundness.
- Contribute to a culture of engineering excellence, mentorship, and team-first collaboration.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
