Lead AI Engineer

ProFound People; Sydney; On-site; AUD 150,000 - 210,000; Full time

Job summary

ProFound People is seeking a Lead AI Engineer to design and ship production-grade AI and agentic capabilities on our platform. This full-stack role emphasizes AI delivery over research, with opportunities to influence backend and occasional frontend work.

You will own the end-to-end lifecycle from design through deployment, including monitoring, edge-case handling, and retraining as usage evolves. Collaboration with data and platform engineers is essential to ensure data quality feeds AI

Qualifications

• Demonstrated experience shipping AI or agentic capability into live production.
• Strong engineering fundamentals: testing, code review, CI/CD, post-release maintenance.
• Experience with LLMs, RAG, or agent-based systems is highly desirable.

Responsibilities

• Design and build production-grade AI and agentic systems integrated in the platform.
• Oversee full lifecycle from design to deployment and post-release monitoring.
• Contribute across backend with occasional frontend work, aligning with data/platform teams.
• Iterate based on real usage and retrain as models or needs drift.

Skills

AI engineering

Production deployment

LLMs

RAG

CI/CD

Frontend exposure

Tools

Git

Docker

CI/CD pipelines

React

Job description

A well funded, fast growing software company has recently taken an AI powered product from concept into live production, used daily by a large and growing customer base.

They are now looking for a Lead AI Engineer to help build the next layer of agentic capability on top of it. This is a full stack engineering role with a strong AI lean, not a data science role.

What you'll own

• Design and build production grade AI and agentic systems that take real actions inside the platform, not internal tools or research prototypes
• Work across the full lifecycle, from design through deployment to what happens after release, including monitoring behaviour and handling edge cases once real users are relying on the system
• Contribute across backend, primarily with occasional frontend involvement
• Collaborate closely with data and platform engineers to keep AI features fed with the right data
• Iterate based on real usage patterns, adjusting or retraining as the system drifts or as user needs shift

What you'll bring

• Genuine experience shipping AI or agentic capability into a live production environment, not just building and evaluating models
• Solid engineering fundamentals, testing, code review, CI/CD, and a track record of maintaining systems after release, not just building them
• Experience with LLMs, RAG, or agent based systems is a strong plus
• Frontend exposure, React or similar, is useful but not essential