Engineering roles are shifting. The day-to-day is now orchestrating AI agents, writing precise specifications, and validating what they produce—but that only works on a solid engineering foundation. You still need to reason about code, debug production issues, and make sound architectural decisions.

"Engineering roles are shifting toward agent supervision, system design, and output review." — Anthropic, 2026 Agentic Coding Trends Report

We're a venture studio that creates AI-powered businesses on enterprise-grade cell-based infrastructure where security, compliance, portability, and transparency are baked in from day one. Agentic workflows have changed how we deliver: POCs that used to take sprints now take hours—throwaway by design, built to validate assumptions and define what the MVP needs. MVPs are then purpose-built from the ground up for production. This rapid POC-to-MVP cycle is the rhythm you'll work in every day.

• Use agentic coding tools (Claude Code, Cursor, Codex) as your primary mode of building—designing specifications, directing agents, and reviewing their output. Know when to code by hand; manual coding is just as important, but agentic workflows drive the day-to-day rhythm
• Write detailed task specifications, tickets, and contractual prompts that translate product requirements into precise agent instructions. Build and maintain agent harnesses—the scaffolding, guardrails, and feedback loops that keep agents productive
• Review and debug AI-generated code with the same rigour you'd apply to human-written code. Implement testing and validation pipelines that catch agent errors before production
• Build responsive web apps (React/Next.js/TypeScript) and server-side systems (Node.js), design API contracts (REST, tRPC, gRPC), and create AI-assisted workflows and multi-agent networks
• Understand and build within cell-based architectures where security, compliance, data isolation, portability, and transparency are structural requirements
• Partner with technical co-founders and UX leads across multiple ventures, context-switching effectively while documenting decisions and agent configurations for the team

"Generative AI will require 80 percent of the engineering workforce to upskill through 2027." — Gartner, October 2024

• TypeScript & React/Next.js — You can build, debug, and reason about modern frontend and full-stack applications
• System design & API contracts — Experience designing scalable systems and typed API contracts (REST, tRPC, gRPC). You understand enterprise requirements like data isolation, audit trails, and compliance-by-design

• Agent orchestration fluency — Demonstrated experience using AI coding agents (Claude Code, Cursor, Copilot, Codex, or similar) as core productivity tools, not just autocomplete
• Specification & prompt design — Ability to write detailed, purpose-driven tickets and contractual prompts that reliably produce correct agent output
• Code review & quality ownership — Ability to read, review, and debug code you didn't write—whether produced by an agent or a teammate—and maintain quality across AI-augmented codebases

• Python for backend services, data pipelines, AI/ML integration, or scripting
• AI orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, MCP) or multi-agent system design
• Familiarity with cell-based infrastructure, zero-trust networking, or compliance-by-design patterns
• Flutter or React Native for mobile (used selectively across some ventures)
• Experience in regulated industries or venture studio / multi-product environments

• Agentic: Claude Code, Cursor, GitHub Copilot, Codex, MCP, Agent Skills
• Frontend: React, Next.js, TypeScript
• Backend: Node.js, tRPC, gRPC, Python, PostgreSQL, Firestore, LangChain/LangGraph
• Infrastructure: GCP, Docker, Kubernetes, Terraform, cell-based architecture, compliance-by-design
• AI/ML: Anthropic Claude, OpenAI, Vertex AI

• 30 Days: Get up to speed on our infrastructure, enterprise patterns, and agentic workflows. Ship your first POC using agent-first methods
• 90 Days: Contribute meaningfully across multiple ventures, take ownership of features end-to-end, and start establishing your agent harness patterns
• 6 Months: Own complex features, contribute to architecture decisions, and help shape how the team works with agentic workflows
  

• Multiplied Impact: Your engineering and orchestration skills launch multiple startups, not just ship one feature
• Enterprise-Grade Environment: Work within infrastructure where security, compliance, portability, and transparency are structural
• Cutting-Edge Practice: Work with the latest agent frameworks, MCP integrations, and Agent Skills—and shape products from concept to launch
• Define the Future Role: Help define what "agentic engineer" means in practice—your experience here will be the blueprint

• Base: $80K–$120K AUD (based on experience)
• Equity: Meaningful ownership in ventures you build
• Benefits: Flexible PTO, professional development budget, remote-first culture

Our process reflects the role—we evaluate your engineering skills and how you work with AI agents.

• Portfolio Review (async) — Share projects demonstrating strong engineering, agentic workflows, AI integration, or multi-product work
• Intro Call (30 min) — Get to know each other and explore fit
• Agentic Challenge (take-home) — Build a small React + API integration using AI agents. We evaluate your engineering decisions, orchestration approach, code review process, and final output quality
• Technical Interview(s) (1–2 rounds) — Architecture discussion, system design, agent workflow walkthrough, code review exercise
• Reference Checks — 2–3 professional references

Email [email protected] with:

• Your resume/CV and a portfolio (especially projects demonstrating engineering depth and agentic workflows)
• A brief note (max 300 words) on how you use AI agents in your development workflow today—and how it complements your engineering skills
• Your timezone and Sydney availability hours

We review weekly and respond within 5 business days. 1QLabs welcomes diverse perspectives. We're building a team of engineers who combine deep technical skill with agentic fluency to shape the future of AI-powered businesses.