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.
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