Perplexity
Member of Technical Staff (Software Engineer, Multimodal)
San Francisco. Posted 2 months ago
The role
You will design and scale distributed systems that carry live voice sessions in production. You will build backend session-worker architecture, orchestration layers, and streaming protocols for multimodal AI experiences.
What you will do
- Design, build, and scale the backend session-worker architecture for realtime voice.
- Own distributed-systems problems including session lifecycle, crash recovery, and multi-region deployment.
- Build provider-agnostic streaming protocols from the backend to the Rust SDK.
- Drive new products and initiatives in voice and multimodal AI from definition to launch.
- Build the orchestration layer for live voice models to delegate work to tools and agents.
- Partner with SDK, client, infrastructure, and model teams.
Required qualifications
- 4+ years of professional software engineering experience building backend or distributed systems.
- Strong experience in Rust, Python, or Go.
- Experience designing and operating production distributed systems including streaming RPC, stateful services, message-driven architectures, and failure recovery.
- Solid understanding of cloud infrastructure such as AWS or equivalent.
- Strong product judgment to translate user problems into technical solutions.
- Genuine interest and adoption of AI products and willingness to learn quickly.
Nice to have
- Experience with realtime media systems: voice, audio streaming, WebRTC, or low-latency transport.
- Full-stack range — comfort building end-to-end, from backend services through client SDKs or web frontends.
- Experience integrating LLMs, speech models, or computer vision into production systems.
- Experience with agent frameworks, tool-calling architectures, or sandboxed execution environments.
- Time spent at a fast-growing startup or on a high-ownership engineering team.
About the company
Perplexity's mission is to power curiosity. The company has scaled into a new paradigm of using AI to transform knowledge into action.