Engineering Manager, (Multimodal)

AI in this role

llm-integrationcomputer-vision

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.

How we score this

Engineering Manager, (Multimodal) at Perplexity scores 69 out of 100 for how much of the daily work is AI. That makes it AI Level 3 of 4 (Works on AI). The level is about AI in the job, not seniority.

Classification

AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

LLM IntegrationComputer Vision

Questions you could be asked

How have you integrated a large language model into a production application?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: LLM Integration and Computer Vision. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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