GM - AI Technical Solutions
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Key details
- Location
- Melbourne, VIC, Australia
- Work style
- Onsite
- Function
- other
- Focus area
- other
- Posted
- 21h ago
Skills
awsllm
About the role
Reporting to the Managing Director, Consumer and Chief AI Officer, you will build Vocus’s in-house AI engineering and science capability and deliver production-grade AI solutions on the agreed platform and make sure what we build is secure, evaluated, reusable and ready for Technology to run.
Key Responsibilities
Lead and develop the AI Technical Solutions team
Own the technical delivery of AI solutions that deliver measurable commercial value
Design and build the agentic platform and enterprise AI architecture
Set engineering, evaluation and AI control standards, in partnership with Security, Legal and Risk
Own the reusable component catalogue, patterns and standards, so each new AI solution is faster and easier to deliver than the last
Build the talent pipeline and career pathways for AI engineers and scientists, reducing reliance on external partners over time
Skills & Experience
Deep background in software or ML engineering, with a track record of leading multi-disciplinary engineering teams
Has shipped LLM or ML solutions into production at enterprise scale
Deep familiarity with AWS; Bedrock or similar agent frameworks strongly preferred
Strong grasp of security, privacy and controls for critical infrastructure
Builds teams and engineering culture.
Key Responsibilities
Lead and develop the AI Technical Solutions team
Own the technical delivery of AI solutions that deliver measurable commercial value
Design and build the agentic platform and enterprise AI architecture
Set engineering, evaluation and AI control standards, in partnership with Security, Legal and Risk
Own the reusable component catalogue, patterns and standards, so each new AI solution is faster and easier to deliver than the last
Build the talent pipeline and career pathways for AI engineers and scientists, reducing reliance on external partners over time
Skills & Experience
Deep background in software or ML engineering, with a track record of leading multi-disciplinary engineering teams
Has shipped LLM or ML solutions into production at enterprise scale
Deep familiarity with AWS; Bedrock or similar agent frameworks strongly preferred
Strong grasp of security, privacy and controls for critical infrastructure
Builds teams and engineering culture.