Software Engineer, Agent Experience at AssemblyAI in North America
- Company: AssemblyAI
- Location: Remote - North America
- Salary: $160K – $210K
- Job type: full time
- Workplace: onsite
- Posted: 2026-10-16
Job description
Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. We have a lab, and we also power our own models in our own proprietary inference environment. Our models serve 500M+ inference calls monthly, and process nearly 2 million hours of audio daily. The Voice AI space is at an inflection point; we’re looking for the best talent we can find to join a rapidly scaling team that's defining the future of the industry. We are one of the most capital-efficient AI companies on the planet - and are rapidly approaching $1M ARR per employee. We sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. We have thousands of customers building with us including the top startups and world-renowned enterprises, and are serving at tremendous scale: we process nearly 2 million hours of audio daily and handle more than 15 million API calls every day. This is a rare growth-stage opportunity where the business is proven, the revenue is durable, and the growth trajectory is steep and getting steeper. We have a super flat culture and expect our employees to be deeply intimate with the details at all levels. If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name. About the role: More and more developers don't read our docs or click through our dashboard. Their coding agent does. Claude Code, Cursor, Codex and others are now how a big share of engineers discover, integrate and debug AssemblyAI. We've spent years polishing the human experience. The agent experience (AX) is newer, growing fast, and almost untouched. That's the job. You'll own how AI agents build with AssemblyAI: the skills, prompts, MCP server, code samples, docs and integrations an agent reads and runs when a developer says "add transcription to my app." Your north star is simple: an agent should go from zero to a working, production-grade AssemblyAI integration on the first try. You'll work closely with senior engineers on our Product Engineering team, with real ownership from day one and room to grow into leading AX as the area scales. What You’ll Do: Drive the agent experience. Treat coding agents as a first-class user of AssemblyAI, alongside the humans who use our dashboard and Playground. Build and maintain agent skills. Ship skills for our core products (Speech-to-Text, Real-time, Dictation, Voice Agents, TTS, LLM Gateway) that teach agents how to integrate us correctly. Build o n our MCP server and agent integrations. Extend the AssemblyAI MCP server, help ship agent and MCP auth (OAuth and API keys), and make it easy to plug into Claude Code, Cursor, Codex and whatever comes next. Make our docs and code samples agent-ready. Own llms.txt, machine-readable docs, quickstarts and SDK examples so agents pick the right API, parameters and patterns the first time. Tune the prompts and instructions behind our product. Improve the system prompts, tool definitions and agent instructions that power our in-dashboard agent and onboarding flows. Measure it. Build evals and benchmarks that run real coding agents against real integration tasks. Track success rate, time to first working call, and activation from agent-driven signups. Help us scale the playbook. Start with one product and then roll what works across every product. Use AI tools as a core part of how you work, and help the rest of engineering build faster with agents. What You’ll Need: 2+ years of profes
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