AI Automation Lead — Intelligent Operations Engineer

Singtel Group; Ryde; Hybrid; AUD 140,000 - 230,000; Full time

Benefits offered by this job

Flexible/hybrid work arrangement (3 in

2 remote days)

On-site childcare centre

Free counselling services

Employee discounts

Parental leave up to 16 weeks

Diversity networks & culture programs

Company bus to Macquarie Uni station

Job summary

Optus is seeking an AI Automation Lead to drive AI innovation across our OSS environment. You will design, build, and deploy AI-powered automation solutions, mentor engineers, and lead delivery with a hands-on engineering approach.

You’ll collaborate with architecture, security, data, and platform teams to ensure scalable, observable, and governance-aligned implementations. A strong background in enterprise AI and modern engineering practices is essential.

Qualifications

• H hands-on experience delivering AI automation within complex enterprise environments.
• Strong technical expertise across APIs, workflow orchestration, CI/CD, event-driven architectures, and LLM integrations.
• Experience with Graph RAG, vector databases, knowledge retrieval, semantic search and metadata management is a plus.
• Excellent stakeholder management and ability to mentor and lead technical teams.

Responsibilities

• Design, develop, and deploy AI-enabled automation solutions and reusable engineering assets.
• Build and maintain Graph RAG, semantic search, knowledge retrieval, and knowledge management capabilities.
• Lead POCs, pilots, and production implementations with governance, observability, and security in mind.
• Provide technical leadership and mentoring to engineers and delivery teams across architecture and security stakeholders.

Job description

Optus is seeking an AI Automation Lead to drive AI innovation across our OSS environment. You will design, build, and deploy AI-powered automation solutions, mentor engineers, and lead delivery with a hands-on engineering approach.

You’ll collaborate with architecture, security, data, and platform teams to ensure scalable, observable, and governance-aligned implementations. A strong background in enterprise AI and modern engineering practices is essential.