Embedded AI Engineer: Production-Ready AI Solutions

Nuix; Sydney; Hybrid; AUD 180,000 - 230,000; Full time

Job summary

Nuix is building an internal AI capability and seeks an AI Enablement Builder who will develop production-grade AI systems within priority business functions. The role combines engineering rigor with business process acumen, delivering end-to-end AI solutions rather than pure advisory work.

The successful candidate will own scoping through post-launch monitoring, work across LLMs, RAG, and agentic workflows, and collaborate with functional leaders in a hybrid Sydney-based setup.

Qualifications

• Production AI systems experience in enterprise environments.
• Strong fluency with Python and AI tooling.
• Ability to translate vague problems into production-ready solutions.
• At least five years software/AI experience with collaboration with non-technical stakeholders.

Responsibilities

• Embed within assigned business functions for rotation periods of three to six months, diagnosing high-value AI opportunities and converting them into production solutions.
• Design, build and deploy end-to-end AI workflows, automations and agentic systems in Nuix's live environment.
• Own the full delivery lifecycle for each use case, from scoping to production deployment and monitoring.
• Maintain POC discipline with time-boxed validation and clear exit criteria.
• Synthesize patterns and contribute findings to Nuix's internal AI knowledge base and programme roadmap.
• Act as a credible technical peer to function leads and AI Advocates, communicating progress to stakeholders.

Skills

Python

Production AI

LLM integrations

RAG pipelines

Agentic workflows

Tools

LLMs

Prompt engineering

RAG pipelines

Agent orchestration

MCP-based tool integration

Job description

Nuix is building an internal AI capability and seeks an AI Enablement Builder who will develop production-grade AI systems within priority business functions. The role combines engineering rigor with business process acumen, delivering end-to-end AI solutions rather than pure advisory work.

The successful candidate will own scoping through post-launch monitoring, work across LLMs, RAG, and agentic workflows, and collaborate with functional leaders in a hybrid Sydney-based setup.