Description

Design and develop autonomous AI agents capable of reasoning, planning, and executing complex tasks. Build adaptive multi-agent systems leveraging natural language understanding and reinforcement learning. Architect end-to-end frameworks for goal-driven collaboration, memory management, and real-time interaction.

Responsibilities

• Architect and implement autonomous agent workflows using LLMs and cognitive components.
• Develop adaptive multi-agent systems with contextual awareness and self-improving behaviors.
• Integrate large language models and reasoning engines for decision-making and task automation.
• Design intelligent memory systems, retrieval mechanisms, and dynamic planning strategies.
• Collaborate with data scientists and ML engineers to define agent workflows for intelligent automation.

Required Skills

• 10+ years of experience in AI development and autonomous systems.
• Deep expertise in agentic architectures and reinforcement learning frameworks.
• Strong hands-on proficiency in Python and AI libraries such as LangChain, AutoGen, and Hugging Face.
• Experience integrating LLMs and orchestration tools for complex task execution.
• Proficiency in designing retrieval-augmented generation (RAG) and dynamic planning strategies.
• Exposure to simulation environments, API integration, and tool augmentation for autonomous agents.
• Ability to translate research insights into production-grade, intelligent systems.

Preferred Skills

• Experience leading research initiatives and publishing frameworks or best practices in autonomous systems.
• Background in building proof-of-concepts for enterprise-level agentic AI applications.

Key Skills

Education

Any Graduate