Principal AI Engineer

At GBST, we're focused on embedding AI across our products, technology operations and business processes. We're looking for a Principal AI Engineer to provide technical leadership and help shape how AI is designed, governed and scaled across the organisation. This is a newly created, strategic, hands-on leadership role where you'll drive the creation of reusable AI capabilities while establishing the standards, frameworks and guardrails that enable responsible AI adoption.

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.

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.