Job description

Full-time Charlotte, NC Responsibilities: Enterprise AI Architecture: • Design and maintain Client's enterprise AI platform architecture • Establish technical standards for AI solution implementation • Define integration patterns for AI services across Client's technology landscape • Create and maintain AI reference architectures, including RAG implementations • Develop model registry and lifecycle management frameworks Technical Leadership: • Lead the technical design of AI platform components and services • Define agent orchestration standards and patterns • Establish guardrails for AI implementation and deployment • Create architectural patterns for knowledge base governance • Guide teams on technical implementation of AI solutions Standards & Governance: • Develop technical standards for AI model deployment and management • Create governance frameworks for AI platform components • Define security and compliance requirements for AI implementations • Establish monitoring and observability standards • Maintain architectural compliance across AI initiatives Solution Design & Review: • Review and approve AI solution designs • Ensure alignment with enterprise architecture standards • Identify opportunities for reusable components • Guide teams on technical implementation approaches • Evaluate new AI technologies and platforms Platform Evolution: • Drive the evolution of Client's AI platform capabilities • Identify and evaluate emerging AI technologies • Define roadmap for platform capabilities and features • Ensure scalability and performance of AI solutions • Guide integration with existing enterprise systems Requirements: • 10+ years of enterprise architecture experience • 5+ years specifically focused on AI/ML platforms and solutions • Strong background in large-scale distributed systems • Experience with major cloud AI services and platforms • Deep understanding of AI security and governance requirements • Expert knowledge of AI/ML architectures and platforms • Strong enterprise architecture capabilities • Deep understanding of security and compliance requirements • Experience with cloud-native architectures • Knowledge of AI model lifecycle management • Expertise in data architecture and integration patterns • Strong technical leadership and communication abilities • Large Language Models and GenAI technologies • RAG architectures and implementation patterns • Cloud AI services (AWS, Azure, GCP) • Enterprise integration patterns • Security and compliance frameworks • Data architecture and governance • Model operations and MLOps

Requirements

Must-haves

Charlotte, NC
Design and maintain Client's enterprise AI platform architecture
Establish technical standards for AI solution implementation
Define integration patterns for AI services across Client's technology landscape
Create and maintain AI reference architectures, including RAG implementations
Develop model registry and lifecycle management frameworks
Lead the technical design of AI platform components and services
Define agent orchestration standards and patterns
Establish guardrails for AI implementation and deployment
Create architectural patterns for knowledge base governance
Guide teams on technical implementation of AI solutions
Develop technical standards for AI model deployment and management
Create governance frameworks for AI platform components
Define security and compliance requirements for AI implementations
Establish monitoring and observability standards
Maintain architectural compliance across AI initiatives
Review and approve AI solution designs
Ensure alignment with enterprise architecture standards
Identify opportunities for reusable components
Guide teams on technical implementation approaches
Evaluate new AI technologies and platforms
Drive the evolution of Client's AI platform capabilities
Identify and evaluate emerging AI technologies
Define roadmap for platform capabilities and features

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimlawsazuregcp

Platform: jobdiva
Effort: medium