Founding Engineer, AI Agents

MIAO WORLDS PTE. LTD.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

MiAO AI is hiring a senior engineer to design the core agent system that bridges model intelligence and product reliability. You will define runtime, orchestration, context, and security boundaries to deliver deterministic agent experiences.

You'll join a small elite team reporting to the founders, collaborating with product and software engineers to set engineering standards and shape the technical roadmap in Singapore.

Qualifications

• 5+ years of software engineering delivering production‑grade agent systems.
• Deep understanding of LLM-driven agent architecture and tradeoffs.
• Expertise in context engineering for optimal decision-making across sessions.
• Experience building across languages (TypeScript, Python, Bash).
• Verification‑first design mindset for reliable systems.

Responsibilities

• Design and build the core agent runtime architecture for thinking, executing, and recovering from errors.
• Design the agent memory and context architecture across sessions.
• Build the agent security layer for sandboxed execution and data privacy.
• Design multi-agent orchestration for task decomposition and result aggregation.
• Define observability and evaluation systems to measure agent reliability.
• Set technical standards and contribute to product strategy and roadmap.

Skills

5+ years software engineering

LLM-driven agent architecture

context engineering

multi-language development

verification-first design

Job description

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.

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)