AI & Agentic Tech Principal

Overview

Define what “good” looks like across data, integration/APIs, security, infrastructure, models, orchestration, and the consumption layer. Maintain a prioritised Agentic AI capability backlog for the domain. Track new tools, models, frameworks, and patterns. Enable higher-quality decisions on Agentic AI and build stronger technical and architectural foundations for scaling Agentic AI. Promote confident and responsible Agentic AI adoption.

Responsibilities

• Define what “good” looks like across data, integration/APIs, security, infrastructure, models, orchestration, and the consumption layer
• A prioritised Agentic AI capability backlog for the domain
• Track new tools, models, frameworks, and patterns
• Higher-quality decisions on Agentic AI
• Stronger technical and architectural foundations for scaling Agentic AI
• Confident and responsible Agentic AI adoption

Qualifications

• Deep, hands-on experience with AI and Agentic AI at scale
• Strong, current expertise in AI and Agentic AI
• Credibility with technical specialists and senior leaders
• Motivated by technical responsibility rather than span of control
• Strong judgement on agentic capability and limits
• Proven ability to influence AI technology approaches
• Skilled at focusing technical discussions on what matters most
• Demonstrated ability to steer difficult decisions through insight and evidence
• A pragmatic engineering mindset

Hard Skills

• AI
• Agentic AI
• data integration
• APIs
• security
• infrastructure
• models
• orchestration
• technical architecture
• scaling

Soft Skills

• credibility
• influence
• judgement
• technical responsibility
• focus
• insight
• evidence-based decision making
• pragmatic engineering mindset

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