AI Deployment Engineer (AI)

TL;DR

AI Deployment Engineer (AI): Designing and scaling advanced AI workflows for customers using Codex to accelerate the software development lifecycle with an accent on technical architecture and customer-facing leadership. Focus on building high-signal prototypes, leading technical workshops, and translating customer insights into product improvements.

Location: Must be based in Sydney, Australia

Company

hirify.global is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

• Serve as the primary technical subject matter expert on hirify.global Codex for a portfolio of customers.
• Design and implement AI-enhanced development workflows from rapid prototyping to scalable production rollout.
• Build high-quality demos, reference implementations, and workflow automations using Codex.
• Lead large-format workshops, technical deep dives, and hands-on enablement sessions for engineering organizations.
• Contribute technical guides, patterns, and best practices to the hirify.global Cookbook.
• Translate high-fidelity product insights from customers into clear product proposals and model feedback.

Requirements

• Must be based in Sydney, Australia
• 8+ years of experience in post-sales engineering or solutions architecture working directly with customers.
• 2+ years of software engineering experience with a strong understanding of the software development life cycle (SDLC).
• Active power user of AI coding tools with a defined perspective on developer productivity.
• Experience delivering high-impact technical training or workshops to engineering teams.
• Ability to communicate complex technical concepts in clear, persuasive written and verbal form.

Culture & Benefits

• Opportunity to work at the forefront of AI research and deployment.
• Collaborative, cross-functional environment working with Sales, Product, and Applied Engineering.
• Commitment to equal opportunity and diverse perspectives.
• Focus on safety, reliability, and operational excellence in AI deployment.