AI Platform Architect - Principal

10+ years of experience in technology architecture, platform engineering, software engineering, data architecture, or related disciplines, including leadership of enterprise-scale technology transformation initiatives.

Demonstrated experience defining and evolving enterprise platform strategies, reference architectures, technology standards, and multi-year roadmaps that enable adoption of emerging technologies across a large organization.

Experience architecting and implementing AI, machine learning, generative AI, or advanced analytics platforms, including governance, security, scalability, operationalization, and risk management considerations.

Demonstrated success partnering across technology, product, data, risk, security, legal, and business organizations to establish operating models, governance structures, and execution frameworks that accelerate adoption and value realization.

Deep understanding of how AI capabilities can be applied across the technology lifecycle, including architecture, software development, testing, operations, platform engineering, and developer productivity workflows.

Demonstrated ability to evaluate, influence, and guide enterprise investments in AI technologies by defining measurable business outcomes, adoption strategies, value realization metrics, and success frameworks.

Experience communicating complex technology strategies, architecture decisions, risks, and tradeoffs to both technical and non-technical audiences, including executive leadership.

Demonstrated ability to influence organizational AI fluency through thought leadership, education, mentoring, architecture guidance, and cross-functional collaboration.

Deep understanding of technology governance, architecture principles, security controls, regulatory considerations, and risk management practices within highly regulated industries.

Experience leading cross-functional architecture efforts across application, data, integration, cloud, security, and AI domains to deliver cohesive enterprise technology capabilities.

Experience architecting enterprise AI platforms leveraging technologies such as AWS Bedrock, OpenAI, Anthropic, or equivalent foundation model ecosystems.

Experience designing and implementing enterprise agent architectures, orchestration frameworks, tool integration patterns, and autonomous workflow capabilities.

Experience designing enterprise knowledge architecture and context management capabilities, including knowledge graphs, semantic models, vector search, metadata platforms, retrieval architectures, and context engineering patterns that enable scalable and trusted AI and agentic systems.

Experience establishing enterprise AI governance, observability, evaluation, security, and model lifecycle management capabilities within highly regulated environments.