Agent Harness Engineer - Core Runtime

NinjaTech AI; Sydney; On-site; AUD 140,000 - 190,000; Full time

Job summary

NinjaTech AI in Sydney is seeking a Core Runtime engineer to own the agent harness that turns our LLMs into reliable, autonomous software.

You will design the run loop, orchestration, and monitoring to keep agents safe across thousands of tool calls, with a strong emphasis on scalability, observability, and fault tolerance.

Join a hands-on, research-driven team building the substrate for the next generation of autonomous AI agents.

Qualifications

• Master's or Bachelor's degree in Computer Science or equivalent practical experience.
• 4+ years building production backend or systems software in Python.
• Strong grasp of concurrency, process supervision, and fault-tolerant design.
• Experience with LLM APIs and agent patterns (tool calling, function calling, streaming).
• Track record of shipping and operating reliable services at scale.

Responsibilities

• Research, design, and build the core run loop and orchestration that power autonomous agents.
• Define how agents manage context, recover from errors, and hand off work cleanly.
• Build rapid prototypes and proofs of concepts to turn harness ideas into shipped product capabilities.
• Stay up-to-date with agent architectures from research and industry, and fold the best ideas into our runtime.
• Design self-healing mechanisms so agents degrade gracefully instead of failing hard.
• Collaborate with cross-functional teams including applied science, product, and integrations.

Skills

Python backend

Concurrency

Fault-tolerant design

LLM APIs

Agent patterns

Education

Master's or Bachelor's in Computer Science or equivalent

Tools

Containerization

Sandboxing

Observability tooling

Job description

NinjaTech AI is a generative AI startup (B2C and B2B) with headquarters in Silicon Valley and offices in Sydney and Vancouver. Backed by Alexa Fund and Samsung Ventures, we are building the autonomous AI agents that let anyone get real work done with generative AI.

Position Overview

We are looking for a Core Runtime engineer to own the agent harness that turns our LLMs into reliable, autonomous software. The harness is the run loop, orchestrator, and monitor that keep an agent working safely across thousands of tool calls and hours of wall-clock time. You will work at the intersection of systems engineering and applied AI, building the substrate that every SuperNinja agent runs on.

Key Challenges & Opportunities

• Design and evolve the agent run loop: context management, turn compaction, and recovery from failed or partial tool calls
• Build the orchestrator that launches, supervises, and hands off long-running background agents without losing state
• Implement the monitoring layer that detects stuck, looping, or runaway agents and intervenes safely
• Own the provider abstraction across model backends (Claude, Codex, and others) so the harness stays model-agnostic
• Make the harness observable end to end with structured telemetry, so failures are debuggable in production
• Keep the loop fast and cheap at scale while it powers millions of daily user interactions

Experience & Education Requirements

• Master's or Bachelor's in Computer Science or equivalent practical experience
• 4+ years building production backend or systems software in Python
• Strong grasp of concurrency, process supervision, and fault-tolerant design
• Experience with LLM APIs and agentic patterns (tool calling, function calling, streaming)
• Track record of shipping and operating reliable services at scale

About The Role

You will report to the engineering lead for agent infrastructure and will have ownership in these areas:

• Research, design, and build the core run loop and orchestration that power autonomous agents
• Define how agents manage context, recover from errors, and hand off work cleanly
• Build rapid prototypes and proof of concepts to turn harness ideas into shipped product capabilities
• Stay up-to-date with agent architectures from research and industry, and fold the best ideas into our runtime
• Design self-healing mechanisms so agents degrade gracefully instead of failing hard
• Collaborate with cross-functional teams including applied science, product, and integrations

What Sets You Apart

• You have built an agent framework, workflow engine, or long-running job system before
• You care about reliability the way SREs do, and you instrument everything
• You can reason about non-determinism in LLM outputs and design around it
• Experience with sandboxing, containerization, or secure code execution
• You move fast on prototypes but know when to harden them for scale

Why Join Us

This is a chance to build the foundation that every one of our agents runs on. The harness is where autonomy is won or lost, and you will own it end to end alongside a team that values engineering rigor and scientific curiosity.