About MiAO AI
MiAO AI was founded in 2025 and is headquartered in Singapore, having raised over SGD 95 million from globally renowned investors. Our founding team previously built large-scale live-service gaming products with over 25 million DAU and 100 million MAU.
Our mission: Let AI discover you.
The next leap in AI isn't about getting smarter — it's about becoming yours. Seventy years of AI research keep proving the same thing: general methods win over clever designs. Models are getting stronger. Protocols are converging. Infrastructure is commoditizing. But one layer remains scarce — the layer that makes AI truly yours.
We're building personal AI agents — an AI that knows you better on day 30 than day 1, not because it got stronger, but because you shaped it.
Our workflow is 100% AI-driven — engineering, product, operations, no exceptions. No middle management. Radically flat. Every team member gets unlimited access to frontier AI models. We spend on efficiency, not process.
Who we're looking for: Believe in the Bitter Lesson — let AI discover, not discover for it.
About This Role
You are the architect between model intelligence and product reliability. You design the entire agent system architecture — from runtime to orchestration, from context engineering to security boundaries — turning emergent model capabilities into deterministic, reliable product experiences. You build the technical foundation the team develops on, and set engineering standards.
You'll join a small, elite core team, reporting directly to the founders, working closely with Product Engineers and Software Engineers.
What You'll Do
- Design and build the core agent runtime architecture — how agents think, execute, verify, and recover from errors
- Design the agent's memory and context architecture — enabling AI to make optimal decisions within limited attention and accumulate understanding of users across sessions
- Build the agent security layer — enabling highly autonomous agents to run safely in sandboxes while protecting user data privacy
- Design multi-agent orchestration — task decomposition, concurrent execution, and result aggregation
- Design the architecture and standards for observability and evaluation systems — defining how to measure and improve agent reliability
- Set technical standards, contribute to product strategy and technical roadmap
You May Be a Good Fit If You...
- Your daily workflow is 100% AI-driven — AI isn't an assistive tool, it's your default way of working
- 5+ years of software engineering experience, having designed and delivered production-grade agent systems or complex distributed systems — not prototypes, but real products serving real users
- Deep understanding of how LLM capabilities shape agent architecture — able to articulate the tradeoffs between different execution strategies
- Deep understanding of context engineering — knowing how to help agents make optimal decisions within limited context
- Able to build efficiently across multiple languages — from web applications to sandboxed execution environments (e.g., TypeScript, Python, Bash)
- Verification-first design instinct — believing that designing "how to verify" is harder than designing "how to execute"
Nice to Have
- Production experience with agent self-evolution, multi-agent orchestration, or MCP server design
- Technical community influence (open source contributions, technical writing, or conference talks)
- Please include your GitHub profile URL in your resume. Applications without one may not proceed to interviews.