Agentic AI Solutions Leader

We are seeking a hands-on and visionary Agentic AI Solutions Leader to design and deliver advanced AI-driven solutions to accelerate enterprise AI transformation by leveraging the continuously evolving AI innovations like Generative AI, Agentic AI, LLMs, Deep Learning, and multi-agent systems. The ideal candidate combines deep technical expertise with solution architecture leadership and strong business orientationto deliverautonomous, intelligent systems, for example, Agent Web, Agent Commerce, and Autonomous Enterprise Workflows, with measurable impact.
Responsibilities:
Architect, design, and implement agent-based AI solutions using Generative AI, LLMs/SLMs, and deep learning.
Design and deliver multi-agent systems for: Agent Web (autonomous enterprise systems like marketplaces for customers, partners and employees), Agent Commerce (AI-driven transaction and decisioning systems), Autonomous workflows ( enterprise process reimagination).
Translate business problems into end-to-end AI solutions, ensuring usability, adoption, and time-to-value.
Design safe and governed agentic systems, including: Human-in-the-loop controls, Observability, auditability, and failure handling.
Drive AI solution delivery aligned to measurable business outcomes (productivity, cost, revenue impact).
Collaborate with cross-functional teams to define solution architecture, standards, and reusable patterns in alignment with product roadmap and release plans.
Mentor engineering teams on agentic design patterns, AI system design, and performance optimisation.
Stay at the forefront of Agentic AI, multi-agent systems, and autonomous decision-making technologies by nurturing a culture of continuous learning and experimentation for business impact.
Ensure end-to-end solution quality, scalability, and maintainability.
Requirements:
Strong foundation in AI/ML, deep learning, and LLM-based systems.
Hands-on experience with: Agentic AI frameworks and multi-agent system design, RAG architectures and vector databases, Python, TensorFlow, PyTorch.
Experience integrating AI into enterprise workflows and business processes.
Experience in exponential engineering - evaluation and adoption of AI native engineering tools for shrinking lead time and cycle time.
Strong understanding of: Agent orchestration, reasoning, memory, and tool usage; scalable system design and distributed computing (e. g., PySpark).
Experience with cloud platforms (AWS, Azure, GCP) and modern MLOps practices.
Proven experience in leading AI solution delivery at scale with real business impact.

Experience
10-14 yrs