AI Architecture and Solution Design
• Define end-to-end architecture for AI and GenAI solutions, including classical ML, NLP, multimodal AI, and agentic systems.
• Design scalable and secure architectures for:
• LLM-based applications
• Retrieval-Augmented Generation (RAG)
• Agentic and multi-agent systems
• Multimodal solutions such as image-to-text, video understanding, and speech-to-text
• Translate business requirements into technical solution designs, architectural blueprints, and implementation roadmaps.
• Ensure AI solutions are aligned with enterprise architecture, cybersecurity, data governance, and compliance requirements.
Stakeholder Engagement
• Engage with business and functional leaders to identify AI opportunities and define high-value use cases.
• Present technical concepts and solution proposals to senior stakeholders in a clear and business-relevant way.
• Support pre-sales, RFI/RFP responses, capability presentations, and client/internal leadership discussions where applicable.
• Act as a trusted advisor on AI strategy, feasibility, scalability, and adoption.
Operational Excellence and Responsible AI
• Define and promote best practices for model deployment, monitoring, MLOps, observability, versioning, and lifecycle management.
• Ensure AI solutions are reliable, explainable where needed, and governed appropriately.
• Promote secure, sustainable, and responsible use of AI technologies across the organization.
• Stay current with emerging AI technologies and evaluate their relevance to business needs.