Top Tech Jobs & Startup Jobs

Own and evolve LiveKit’s developer-facing website by building high-performance web experiences, reusable brand components, motion systems, and launch pages. Translate brand and design concepts into polished production code, maintain strong performance budgets, and collaborate closely with designers, marketers, and engineers. The role emphasizes front-end engineering, animation, interaction design, speed, and self-directed delivery.

Lead brand design across campaigns, events, digital, print, out-of-home, presentations, environmental graphics, and physical goods. Develop creative concepts through production, extend LiveKit’s identity across new formats, and maintain a high bar for craft and consistency. Partner with marketing and sales to turn ambiguous briefs into shipped work quickly. Use AI tools throughout the creative process and contribute strong systems thinking, visual direction, and execution.

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.

Own GTM strategic finance for a usage-based AI infrastructure business. Responsibilities include consumption revenue forecasting, deal desk governance, pricing and margin oversight, sales compensation design, quota setting, financial modeling, annual planning, and GTM KPI analytics. The role partners closely with GTM leadership and Finance to advise on investments, deals, forecasting, and business strategy while building scalable financial frameworks.

Own LiveKit Startups end to end, including program design, founder acquisition, accelerator and fund relationships, partner negotiations, application operations, provisioning, reporting, and monthly execution. Track program health and founder outcomes while representing startup feedback internally to product, documentation, and pricing teams. The role requires experience building startup or developer ecosystem programs, commercial partnership skills, technical credibility with developers, and strong operational rigor.

Design and implement real-time audio, video, and voice AI applications with customer engineering teams. Build integrations, prototypes, reference implementations, and scalable architectures; support SDKs, APIs, infrastructure, and deployment strategies; troubleshoot production issues; lead technical workshops; and provide customer insights to Product and Engineering. Contribute to LiveKit’s developer experience, tooling, documentation, and open-source ecosystem. Fluency in Spanish and English is required.

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.

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.