AI Architect

About the role

The AI Architect maintains architectural coherence across GCS AI and Frictionless Time to Value (FTTV) initiatives. The role works at the front end of the process, taking part in use-case and initiative shaping, backlog review and initial solution definition before significant engineering effort is committed. It is a Senior Lead-level individual contributor role that does not manage an engineering squad and does not replace AI Engineering accountability for detailed design, implementation, code quality, production readiness or delivery assurance.

Key responsibilities

• Review and shape the GCS AI backlog and FTTV initiatives, identifying duplicate, overlapping or unclear proposals and working with business stakeholders and AI Engineering to refine use cases and dependencies.
• Promote reuse of existing services, integrations and knowledge assets, and define connection points between solutions.
• Work with AI Engineering leads and developers to define practical architecture standards, reference patterns and reusable approaches, and document justified exceptions.
• Ensure the right specialist perspectives are involved early, covering security, privacy, responsible AI, enterprise architecture, data, integrations, infrastructure, business processes and product platforms.
• Validate designs by prototyping concepts, inspecting implementations or building reference examples, and document key architecture decisions.
• Assess whether solutions support the intended direction of GCS business processes and tooling, and expose unresolved process or tooling dependencies.

Required profile

• Significant experience in software, solution, application, integration, data or AI architecture across multiple applications or teams.
• Experience shaping technical solutions before implementation and defining architecture standards with engineers.
• Ability to explain technical trade-offs to engineering, business and leadership audiences and to work through influence without line authority.
• Hands-on capability to prototype and validate architectural assumptions; experience at Senior Lead, Principal or equivalent individual-contributor level preferred.

Required skills

• Practical experience with AI-enabled applications, including large language models, retrieval-based solutions, agentic systems and structured and unstructured knowledge.
• Strong understanding of modern software architecture, APIs, distributed systems, cloud services, identity, security and integration approaches.
• Preferred: Azure AI services, Azure OpenAI, Azure AI Foundry, API-first, event-driven, microservice and cloud-native patterns, and enterprise AI applications in production.