Engineering Manager (Multimodal)

Perplexity AI; Iowa (LA); On-site; USD 140,000 - 210,000; Full time

Job summary

Perplexity AI is seeking an Engineering Manager for Multimodal to lead realtime voice and multimodal experiences. You will hire and develop engineers, set technical direction, and drive new products at the intersection of voice, vision, and agents.

You will own the team's roadmap, shape the architecture from user utterance to model responses, and partner with SDK, client, infrastructure, and model teams to scale across our apps. Strong leadership and cloud experience are essential.

Qualifications

• Experience leading teams to ship complex projects in fast-moving environments.
• Strong product judgment and ability to translate user problems into technical priorities.
• Experience designing and operating production services on cloud infrastructure.

Responsibilities

• Lead the Multimodal team delivering realtime voice and multimodal experiences.
• Own the team's roadmap and technical direction.
• Hire, coach, and develop engineers while maintaining high-performance standards.
• Collaborate with SDK, client, infrastructure, and model teams to scale features across apps.

Skills

Team leadership

Product judgment

Strong communication

Real-time systems experience

Cross-team coordination

Tools

AWS

Rust

Python

WebRTC

Job description

• 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
• 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

• 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
• Experience designing and operating production services in rapidly scaling environments on AWS or similar cloud infrastructure
• 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
• A strong software engineering background in backend or distributed systems
• Experience managing engineering teams, including hiring, coaching, and performance management
• Clear communication and the ability to work effectively across teams
• Experience with realtime media systems: voice, audio streaming, WebRTC, or low-latency transport
• Experience with agent frameworks, tool-calling architectures, or sandboxed execution environments
• Experience integrating LLMs, speech models, or computer vision into production systems
• 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