Overview
Designs, develops, and deploys autonomous AI systems that can reason, adapt, and act independently to achieve goals.
- Implementing agentic frameworks like LangChain or custom solutions for agent-to-agent communication, dynamic task assignment, and context-aware decision-making.
- Working experience with LLMs (LLaMA, GPT) for language understanding, generation, and task planning.
- Developing and integrating Retrieval-Augmented Generation (RAG) pipelines to enhance agents' reasoning capabilities by grounding them in domain-specific knowledge.
- Implementing multi-agent communication protocols for agent collaboration and coordination.
- Deploying scalable AI workflows on cloud platforms like AWS, Azure or GCP, optimizing for latency and resource utilization.
Skills
- Strong programming skills in Python and experience with object-oriented languages like Java.
- Proficiency in using agentic frameworks and libraries like LangChain, AutoGen, or LlamaIndex.
- Experience with AI and machine learning concepts.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Familiarity with LLMs and their application in agentic systems.