Design and Develop AI Agents: Build intelligent, autonomous agents leveraging LLMs, memory frameworks, and multi-agent coordination systems (e.g., LangChain, CrewAI, AutoGen).
Integrate APIs and Tools: Connect agents with third-party APIs, knowledge bases, and internal systems to enable dynamic data access and real-time task execution.
Optimize Agent Performance: Apply reinforcement learning, context management, and retrieval-augmented generation (RAG) techniques to enhance reasoning and accuracy.
Develop End-to-End Pipelines: Create scalable, production-ready pipelines for AI agent deployment, monitoring, and continuous improvement.
Collaborate with Cross-Functional Teams: Partner with product managers, ML engineers, and domain experts to translate business use cases into functional agentic systems
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
4+ years of experience in AI/ML or software development with hands-on exposure to LLMs.
Strong proficiency in Python and experience with AI frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI.
Experience working with LLM APIs (OpenAI, Anthropic, Google Gemini, etc.) and vector databases (Pinecone, Chroma, FAISS).
Knowledge of agent orchestration, prompt engineering, and context memory management.
Familiarity with cloud environments (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Top Skills
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