Why were hiringWere doubling down on creation quality and reliability. This is a key role with real ownership: youll run the lane end-to-end and set the technical bar for agent-driven app generation. We want people who think in systems, not solutions.How do we generate fully autonomous software for recreational use? How do we generate it fast? And how do we do it tastefully? This role lives at the bleeding edge of what current AI can do - if those questions excite you, its for you.

You will ownDesigning and owning our agent harness layerBuilding long-horizon agentic workflows with maximal autonomyDeveloping robust evaluation and quality loops, including eval harnesses, regression testing, and failure taxonomiesDesigning model strategy: routing, benchmarking, reliability, and cost/latency optimizationCreating debuggable agent systems with tracing, metrics, alerts, and observabilityResearching novel approaches and shipping them to productionWere looking forYouve built agentic systems - tool use, orchestration, retry/repair loops, context management - whether on raw provider APIs or frameworks like LangGraph, PydanticAI, Google ADK, Pi-mono, or Vercel AI SDK. You understand the tradeoffs well enough to know when the framework gets in your way.Experience with distributed / real-time systemsA research-and-ship mindset: you treat open-ended problems as experiments, and you care as much about getting the result into production as discovering itStrong software engineering fundamentals, with depth in Python and/or TypeScriptA track record of shipping and operating production systemsA history of owning hard problems end to end - you can point to systems you built and the outcomes they drove, not just the tech you touchedStrong product instincts: you can translate user-experience goals into system-design decisionsBonus pointsTook a customer-facing product from 0 to 1Built a coding agent, devtool, IDE assistant, or code-generation pipeline (directly relevant - this is what we do)Built evaluation frameworks (automated scoring, regression suites, release gating)Designed MCP-style tool protocols or robust tool interfaces for LLM systemsExperience training and/or fine-tuning LLMsCompensation & benefitsCompetitive compensation: salary + equityFull medical / health insurance coverage health insurance

If you are excited about building at the frontier of AI, consumer social, and interactive entertainment, we would love to hear from you.

At Sekai, you will work with an AI-native team, move fast, own meaningful problems, and have the flexibility to explore new ideas from an early stage.