• Architect and design enterprise-scale agentic AI platforms, frameworks, and multi-agent workflows • Create modular, interoperable, and future-ready AI architectures that integrate seamlessly with existing enterprise systems • Lead design of LLM-based applications, RAG systems, multi-agent planning, and autonomous process automation • Establish architectural standards, design patterns, and reusable components for AI/ML workloads • Oversee end-to-end implementation of AI/ML and agentic systems, including data pipelines, model training, evaluation, and deployment • Work closely with engineering teams to ensure delivery of high-performance, scalable, and cost-optimized AI workloads • Provide technical leadership for model fine-tuning, orchestration, guardrails, and inference optimization • Design secure, compliant, and policy-aligned AI systems with strong guardrails, monitoring, and fallback mechanisms • Integrate AI agents and LLM-driven solutions into enterprise applications, APIs, workflow engines, and automation tools • Define governance frameworks for model lifecycle management, reliability, safety, and performance tracking • Work with business and technology leaders to translate strategic goals into actionable AI roadmaps • Advise on platform choices, toolchains, and cloud/edge deployment patterns • Prepare technical documents, architectural blueprints, and decision frameworks for leadership • Guide data scientists, ML engineers, and developers on solution design, implementation, and best practices • Conduct reviews, coach teams, and ensure adherence to ML engineering and MLOps standards