# Staff Product Manager, Inference

**Company:** [LiveKit](https://hotfix.jobs/companies/livekit)
**Location:** Remote
**Role:** Product Management
**Salary:** $225k – $265k/yr
**Experience:** 8+ years
**Skills:** Product Management, model serving, model routing, latency optimization, ai/ml platforms, inference apis, model benchmarking, ttft, stt, tts, LLMs, realtime models, voice ai, usage-based pricing
**Posted:** 2026-07-27

> Own the product vision and roadmap for LiveKit Inference, the managed gateway for voice AI models. Set strategy on models/providers, drive technical tradeoffs in serving/routing/latency/cost, and make it the default choice for developers over direct provider integrations. Requires 8+ years PM experience with deep technical understanding of AI infrastructure.

## Job Description

## Responsibilities
- Own the LiveKit Inference roadmap: set a clear vision and sequenced plan for the product, decide what gets built and when in partnership with engineering.
- Ship a model layer which developers reach for by default: make accessing the best models through LiveKit easier, faster, cheaper, or better than integrating providers directly, and keep raising the bar.
- Keep pace with the model landscape: decide which models, providers, and modalities to add and when, so LiveKit stays ahead of a fast-moving space.
- Grow the value we deliver and capture: consolidate model spend onto LiveKit in a way that raises the value customers get without raising their cost.
- Get deep with customers and data: understand how teams actually use models in production, and let that shape priorities.

## Requirements
- 8+ years in product management, at a senior or staff level, ideally having owned a developer-facing API, platform, or AI/ML product.
- Technical depth: ability to reason about model serving, routing, latency, and quality tradeoffs, and earn the trust of strong engineers. Understand systems well enough to make good tradeoffs (no coding required).
- Infrastructure and tradeoff sense: experience owning a product where cost, performance, and vendor/provider tradeoffs were central; ability to keep a product current as the landscape shifts.
- Cross-functional influence: influence engineering teams through clarity, trust, and good judgment (teams operate with high autonomy).
- Communication as a superpower: write clearly, present well, and move between board-level strategy and detailed technical discussions.
- Comfort with ambiguity: figure out what matters, prioritize ruthlessly, and move quickly without perfect information in a small, fast-growing product team.

## Nice-to-Haves
- Built a model gateway, inference API, model-provider product, or AI/ML platform.
- Familiarity with model benchmarking and how both performance and quality are measured (e.g. TTFT).
- Familiarity with the STT, TTS, LLM, and realtime model space and top providers.
- Background at a developer tools, API infrastructure, or AI/ML company.
- Familiarity with voice AI, real-time communication, or telephony.
- Experience with usage-based pricing models and cost or margin optimization.

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