Jobs at LiveKit

Own and engineer the GTM stack: Salesforce as system of record and HubSpot as marketing system, build and maintain integrations and data flows, deploy agentic AI workflows, implement observability and change management, and partner with Sales, Marketing, Analytics, and Billing to ensure reliable revenue operations.

As a Distributed Systems Engineer, you'll design and evolve LiveKit's core systems, implement resilient architectures, and enhance reliability and developer velocity, working on critical features in production environments.

Lead security across applications, services, infrastructure, and developer workflows. Identify, assess, and mitigate risks; run secure code reviews, threat modeling, and architecture discussions; build automation and tooling to prevent issues; harden authentication and access control; investigate incidents and manage disclosures; partner with engineering teams to design secure-by-default APIs and deployments.

The Senior Infrastructure Engineer will manage and scale LiveKit's core infrastructure, focusing on reliability and performance, while working on Golang code and automation for distributed systems.

Own the LiveKit Telephony product roadmap, covering SIP trunking, native phone numbers, carrier relationships, global expansion, interoperability, reliability, call quality, pricing, packaging, and margins. Partner closely with engineering, enterprise customers, and carriers to prioritize features, improve production call experiences, establish regulatory coverage, and scale telephony infrastructure for voice AI applications.

Build post-training infrastructure for voice and text agents, including training environments, verifiers, synthetic data pipelines, evaluations, and end-to-end experiments. Select and adapt open-weight models, design robust rewards, deploy models to production, and improve behavior using real-world usage. The role requires strong Python engineering, experience taking models from raw data to production, GPU familiarity, and collaborative remote work.

The Senior Product Engineer will build web and CLI interfaces for developers using LiveKit, focusing on product experience and user feedback. Responsibilities include writing production code, engaging with customers, and making product decisions to enhance developer experience.

Lead LiveKit’s Product-Led Growth squad across acquisition, onboarding, activation, adoption, retention, and expansion. Own the end-to-end developer growth experience, identify high-potential accounts, deepen platform usage, represent self-serve developers, and establish operating metrics for platform health. Partner closely with product, engineering, design, marketing, analytics, support, and sales while influencing strategy in a fast-growing, ambiguous environment.

Own the LiveKit Inference product: set vision and roadmap, decide which models/providers to offer, ship a default model gateway, optimize for cost/latency/quality, engage customers and data, and grow revenue by consolidating model spend onto LiveKit.

Design and evolve core control, data, and observability systems; implement resilient region-spanning architectures; build libraries, protocols, and tooling; diagnose and harden critical paths using metrics, tracing, and testing; and shape platform capabilities across identity, scheduling, observability, and distributed state management.

As a Staff Rust SDK Engineer, you will design, build, and maintain the LiveKit Rust SDK and core modules, leading engineering practices while collaborating across teams to optimize performance and developer experience for real-time applications.

Build and operate internal IT systems across identity, endpoints, Google Workspace, Slack, SaaS governance, and automation. Own Okta access engineering, Workspace ONE macOS fleet management, lifecycle workflows, compliance controls, audit evidence, and technical escalations. Partner with Security, Engineering, People, and Finance to improve security, reliability, and scalability while reducing manual IT support through automation.

Design and implement the core components of the Agents Python framework, focusing on API and abstraction development for AI-driven applications.