• Embed with strategic enterprise customers to rapidly diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site. • Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications. • Drive rapid prototyping and POCs that demonstrate tangible business value within days to weeks. • Serve as the primary technical owner across the full project lifecycle: scoping, architecture, build, deployment, and post-launch optimization. • Architect production-grade Enterprise AI applications on Partner Foundry Solutions or Datacentres Private Cloud and GPU infrastructure, integrating with enterprise systems (ERP, CRM, data warehouses, data lakes). • Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases (Pinecone, Weaviate, AstraDB), and knowledge base frameworks. • Develop and fine-tune LLM/SLM solutions; implement RAG architectures (LlamaIndex, Haystack) and orchestrate multi-agent workflows (LangChain, LangGraph, CrewAI). • Ship with full-stack and DevOps depth: Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management. • Champion observability, monitoring, and telemetry to ensure trustworthy, auditable, and versioned AI agents in production. • Identify expansion opportunities by working with sales and customer success to uncover high-value use cases across new business domains. • Feed structured field insights back to Platform Engineering and Product on feature gaps, emerging needs, and usability improvements. • Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that scale future engagements. • Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies.