Remote AI Product Engineer: Enterprise Multi-Agent Systems

Jobgether; Australia; Remote; AUD 294,000 - 440,000; Full time

Benefits offered by this job

Competitive salary

Fully remote across four continents

Stock options with 10-year exercise

Paid time off: 18 days + 11 holidays

Sick leave

Health insurance + 401(k)

AI tools stipend

Annual in-person offsites

Collaborative engineering culture

Job summary

Partner Company in Australia seeks a Staff AI Product Engineer to shape a next-generation AI product ecosystem for business operations. You will own the architecture of production-grade agentic systems, including MCP integrations, contextual memory, and evaluation frameworks.

You will collaborate with engineering leadership, product teams, and customers to define the technical roadmap, set engineering standards, and accelerate AI-driven workflows in a fast-moving startup environment.

Qualifications

• 7+ years of full-stack software development experience, ideally B2B SaaS.
• Hands-on experience designing and deploying production-grade multi-agent systems.
• Experience building MCP servers or integrations for production use.
• Strong production engineering principles: reliability, observability, security, permissions, safe execution.

Responsibilities

• Lead architecture, design, and development of a production-grade multi-agent system.
• Own MCP integrations connecting internal systems to external AI environments.
• Design unified data infrastructure for AI agents and tools.
• Build contextual memory and customer profiling systems.
• Establish reliability, observability, and safe execution for real customer data.
• Develop evaluation frameworks and automated tests for agent performance.

Skills

React

TypeScript

Node.js

PostgreSQL

GraphQL

LangGraph

Full-stack

Job description

Partner Company in Australia seeks a Staff AI Product Engineer to shape a next-generation AI product ecosystem for business operations. You will own the architecture of production-grade agentic systems, including MCP integrations, contextual memory, and evaluation frameworks.

You will collaborate with engineering leadership, product teams, and customers to define the technical roadmap, set engineering standards, and accelerate AI-driven workflows in a fast-moving startup environment.