AI Solution Architect (SME)

Our enterprise clients are moving from isolated AI initiatives to organization-wide AI platforms that must integrate with complex legacy systems, governance models, and business processes. The challenge is no longer choosing models, but designing coherent, scalable AI architectures that deliver long-term business value.

This role exists to translate strategic AI ambitions into executable, enterprise-grade architectures., You will operate as a Subject Matter Expert responsible for designing end-to-end AI architectures across data, models, platforms, integration, and security layers.

Acting in strategic consulting engagements, solution delivery programs, or product platform initiatives, you will define AI architectures that are scalable, governable, and aligned with enterprise and regulatory constraints., AI Architecture Design (Core)

• Design end-to-end AI architectures from data ingestion to inference and integration
• Define reference architectures and reusable AI platform patterns
• Select appropriate AI technologies based on performance, cost, and governance constraints
• Ensure architectural consistency across multiple AI initiatives

Enterprise Integration & Alignment

• Integrate AI platforms with existing enterprise systems and workflows
• Align AI architectures with enterprise IT, security, and data standards
• Collaborate with business stakeholders to translate requirements into technical designs
• Ensure AI solutions are aligned with long-term platform strategies

Technical Governance & Leadership

• Act as architectural authority for AI solutions
• Review and validate technical designs and implementation choices
• Define non-functional requirements: scalability, resilience, security, observability
• Support delivery teams during implementation and scaling phases

Technical Scope

Architecture Domains

• Data platforms and AI pipelines
• Model training, serving, and lifecycle management
• Integration patterns and API design
• Security, IAM, and compliance architecture

Technology Awareness

• Open-source and proprietary AI platforms
• Cloud, hybrid, and on-prem architectures
• Platform engineering and MLOps foundations

Production Awareness

• Enterprise-grade SLAs and reliability constraints
• Cost and scalability trade-offs
• Long-term maintainability and evolvability

• Strong background in solution or enterprise architecture
• Proven experience designing complex, large-scale systems
• Exposure to AI, data platforms, or advanced analytics in production

Mindset

• Systems-thinking and strategic orientation
• Strong communication and stakeholder alignment skills
• Ability to bridge business strategy and deep technical design
• Pragmatic, outcome-driven approach to architecture