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teamtailor

Principal AI Engineer

GBST
Sydney, AUS
Senior
Hybrid
Discovered 2 weeks ago

Full Job Posting

What you'll be doing

Drive AI capability across Technology Operations

Working closely with Technology Operations, Architecture and Engineering teams, you'll ensure AI solutions align with GBST's technology strategy and enterprise architecture principles. You'll lead the development of reusable AI assets that accelerate delivery and improve engineering productivity across GBST, including:

AI Agents, Custom Agents, Skills and MCP-enabled solutions

RAG architectures, Knowledge Bases and Prompt Libraries

Shared frameworks, patterns and AI accelerators

Standards that promote reuse and consistency across teams

Establish Responsible AI standards and governance

You'll define the technical frameworks, standards and guardrails that ensure AI solutions are secure, scalable and fit for enterprise adoption. This includes leading the development of:

Responsible AI principles and engineering standards

AI architecture patterns and governance frameworks

Security, observability and auditability controls

AI-enabled SDLC and specification-driven development practices

Risk, compliance and privacy-aligned AI solutions

Evaluate emerging AI technologies, conduct technical assessments and help shape GBST's enterprise AI strategy.

What We're Looking For

We're seeking a highly credible technical leader with deep software engineering experience and a passion for building enterprise-scale AI capability. You'll likely bring:

Extensive software engineering and solution architecture experience within complex enterprise environments.

Strong experience designing and delivering AI, Generative AI and Agentic AI solutions.

Experience building reusable AI capabilities including Agents, Skills, Knowledge Bases, RAG solutions and AI accelerators.

A strong understanding of enterprise architecture, integration patterns and modern software engineering practices.

Experience defining engineering standards, frameworks and governance models.

Deep knowledge of Responsible AI, AI security, observability, risk management and governance controls.

Proven ability to influence senior technology stakeholders and drive adoption of engineering standards across multiple teams.

Experience working with modern AI ecosystems, LLM platforms, agent frameworks and emerging AI technologies.

Qualifications

  • Extensive software engineering and solution architecture experience within complex enterprise environments.
  • Strong experience designing and delivering AI, Generative AI and Agentic AI solutions.
  • Experience building reusable AI capabilities including Agents, Skills, Knowledge Bases, RAG solutions and AI accelerators.
  • A strong understanding of enterprise architecture, integration patterns and modern software engineering practices.
  • Experience defining engineering standards, frameworks and governance models.
  • Deep knowledge of Responsible AI, AI security, observability, risk management and governance controls.
  • Proven ability to influence senior technology stakeholders and drive adoption of engineering standards across multiple teams.
  • Experience working with modern AI ecosystems, LLM platforms, agent frameworks and emerging AI technologies.

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