Key Responsibilities

• Design, prototype, and implement cutting-edge autonomous AI agents and multi-agent systems capable of dynamic planning, reasoning, memory management, and self-reflection.
• Develop and integrate core agent components, including planning modules (e.g., Tree-of-Thought, CoT-based planners), tool-use interfaces, and persistent long-term memory/retrieval mechanisms (RAG).
• Develop high-quality, production-ready code in Python/Go for integrating LLMs and other foundational models into functional agent architectures.
• Build and maintain scalable agent infrastructure using frameworks like LangChain ensuring seamless integration with cloud services (AWS preferred).
• Conduct rigorous testing, evaluation, and optimization of agent performance on complex, real-world tasks.

Work closely with the engineering team to define agent use cases and translate research prototypes into deployable product features that deliver business value.