In 2026, we launched Computer, the defining product for the new era of agentic AI. We've scaled beyond the millions of people using Perplexity every day for research, shopping, investing and curiosity into a new paradigm of using AI to transform knowledge into action.
The Multimodal team builds the experiences and infrastructure that move AI interaction beyond touch and text: realtime voice, vision, and the platform systems behind them. We own the full path from a user speaking into a device to an answer coming back: the realtime session infrastructure that connects clients to frontier audio models, the backend orchestration that routes, records, and supervises live sessions, and the SDK that powers voice and multimodal experiences across Perplexity's apps.
As Engineering Manager for Multimodal, you will lead the team building realtime voice and multimodal experiences across Perplexity. You'll hire and develop engineers, set technical direction, and drive new products at the intersection of voice, vision, and agents.
Key Responsibilities
Lead the team building realtime voice and multimodal experiences across Perplexity, taking new products from first prototype to production launch.
Own the team's roadmap, deciding which voice and vision experiences to build next and what infrastructure they need to succeed.
Hire and develop engineers, giving them ownership of meaningful technical problems and the feedback to grow.
Shape the architecture behind the full voice experience, from a user speaking into a device to models, tools, and agents responding.
Lead the systems that turn live conversations into action, connecting voice models to tools, agents, and long-running tasks.
Guide the team through the latency, reliability, and scaling challenges of live voice, including session recovery and performance under load.
Partner with SDK, client, infrastructure, and model teams to turn new audio and vision capabilities into experiences people can use across our apps.
Use user feedback and production performance to improve the experience after launch and decide where the team should invest next.
Qualifications
Experience managing engineering teams, including hiring, coaching, and performance management.
A strong software engineering background in backend or distributed systems.
Experience designing and operating production services in rapidly scaling environments on AWS or similar cloud infrastructure.
A track record of leading teams to ship complex projects in a fast-moving environment.
Strong product judgment and the ability to translate user problems into clear technical priorities.
Clear communication and the ability to work effectively across teams.
Experience with Rust, Python, Go, or similar languages. We work primarily in Rust and Python.
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.
Experience integrating LLMs, speech models, or computer vision into production systems.
Experience with agent frameworks, tool-calling architectures, or sandboxed execution environments.
Experience leading projects across backend services, client SDKs, and user-facing applications.
Time spent leading a team at a fast-growing startup or in a high-ownership environment.