AI Solution Architect Leader
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Key skills for this role
About the Role
Own and define end to end AI solution architectures spanning data platforms, AI/ML pipelines, GenAI/LLM stacks, cloud infrastructure, security, integration, and MLOps Act as des.
Key Skills for This Role
Full Job Posting
Overview
Own and define
end to end AI solution architectures
spanning data platforms, AI/ML pipelines, GenAI/LLM stacks, cloud infrastructure, security, integration, and MLOps
Act as
design authority
for large scale, multi vendor AI programs, ensuring architectural coherence and compliance with enterprise, data, security, and regulatory standards
Lead delivery of AI solutions, directing internal teams and partners to meet performance, scalability, reliability, and responsible AI requirements
Translate business requirements into actionable AI designs, including model selection, orchestration patterns, human in the loop workflows, and system integrations
Chair AI architecture reviews and governance forums, communicating complex technical concepts effectively to executive and non technical stakeholders
Oversee AI solution quality, risks, and dependencies, including data readiness, model risk, technical debt, and ethical AI considerations
Originate and shape
AI led opportunities
across priority industries and strategic accounts
Lead AI solutioning for proposals, bids, and competitive pursuits
Act as a trusted advisor to client executives on
AI strategy, investment prioritization, and value realization
Represent the organization in client workshops, executive briefings, and selected thought leadership engagements
Build and scale the firm s
AI solution architecture capability
, including reference architectures, accelerators, and delivery playbooks
Deep expertise in
enterprise AI solution architecture
, including data platforms, ML engineering, GenAI/LLMs, cloud services, security, and MLOps
Proven ability to take AI solutions from
pilot to production at enterprise scale
Strong command of AI non functional requirements: performance, reliability, explainability, compliance, and cost optimization
Hands on experience with modern AI platforms, open source ML frameworks, vector databases, and orchestration/monitoring tools
Executive level communication and influencing skills, bridging business strategy and advanced AI engineering
Strong understanding of
responsible AI
, governance, and regulatory considerations
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