> Markdown version of [/jobs/ext/2718741-full-stack-engineer](https://www.wearedevelopers.com/jobs/ext/2718741-full-stack-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full-Stack Engineer - **Company:** PLAUD INC. - **Location:** San Francisco, CA, United States - **Salary:** $140,000.0 - $172,000.0 - **Contract:** Permanent contract - **Skills:** Flutter, Java (Programming Language), Artificial Intelligence, Application Integration Architecture, Systems Engineering, Automation of Tests, C++ (Programming Language), Code Review, Databases, Continuous Integration, Data Structures, Software Debugging, Distributed Systems, Python (Programming Language), Online Service Provider, Performance Tuning, Systems Integration, TypeScript, Management of Software Versions, Web Applications, WebRTC, Core Voice Platform, Data Logging, ReactJS, Large Language Models, Caching, Audio Streaming, Backend, Low Latency, Data Analytics, React Native, Front End Software Development, Api Design, Golang, Microservices - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/full-stack-engineer-palo-alto-plaud-8696908 ## About the Role Strong Engineering Execution (Required) * Proven track record of owning and delivering critical systems/components end-to-end (we value demonstrated delivery and depth over a specific number of years) * Solid CS fundamentals: data structures, algorithms, system design * Consistently high-quality output in fast-paced environments Backend / Distributed Systems (Required · Primary) * Proficiency in at least one backend language (Python, Go, Java, C++, etc.) * Experience building scalable online services: API design, async workflows, microservices * Familiarity with distributed systems fundamentals: databases, caching, messaging, performance optimization Strong AI Sense & Hands-On Practice (Required · Emphasis) * Not just "interested" - you've actually built products with LLMs / Agents / workflow automation * Ability to turn prototypes into scalable, maintainable, production-ready solutions * You already use AI tools in your day-to-day work Production Engineering Excellence * Experience delivering production systems with a focus on reliability, latency, and scalability * Knowledge of observability best practices: logging, monitoring, alerting, tracing * Engineering rigor via automated testing, CI/CD, and disciplined code review Ownership & Cross-Functional Collaboration * Strong end-to-end ownership; effective under ambiguity * Proven ability to work with Product, Applied AI, and GTM toward shared outcomes * Accountable for user experience and delivery impact Strong Plus * Mobile (emphasis): native iOS / Android, or cross-platform (Flutter / React Native); able to ship mobile features or maintain a mobile SDK independently * SDK Development (emphasis): designing, packaging, versioning, and delivering developer-facing SDKs, with a focus on usability and integration experience * Realtime / Audio: WebRTC, audio streaming, low-latency transport * Voice AI: ASR / TTS pipelines, voice Agents, cascade vs. native speech-to-speech architectures * Frontend (nice-to-have): familiarity with React / TypeScript; able to contribute to web apps or developer consoles ## Description * AI Application & Backend Core Delivery: Engineer and iterate realtime voice AI services and Agent workflows; build key modules including tool orchestration, memory, and multi-step reasoning; translate business requirements into scalable service capabilities. * Production-Grade System Engineering: Design and implement highly-available, low-latency, scalable architectures (latency is especially critical for realtime voice); establish monitoring, logging, alerting, and tracing foundations to support both high-frequency consumer usage and enterprise deployment. * AI Integration & Closed-Loop Iteration: Integrate LLM / ASR / TTS capabilities into product pipelines; help build evaluation frameworks and automated testing for Agent and voice quality; partner with Applied AI and Product to drive data-driven, closed-loop improvement in production. * Full-Stack Collaboration & Rapid Iteration: Keep backend as your main line while extending into mobile, SDK, or frontend surfaces as needed to ship end-to-end; collaborate closely with Product, Applied AI, and mobile teams across enterprise PoCs and consumer features. * AI-Native Engineering Velocity: Actively adopt AI coding assistants, agentic dev workflows, and automated testing/debugging tools to accelerate iteration while maintaining strong engineering quality. ## Related Videos - [User 1st! 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