Work Experience
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
- 5+ 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 or AutoGen, CrewAI, Agentic Ai AI Agents, Google ADK LangGraph and n8n
- 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).
Responsibilities
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
Skills: google,aws,data,management,access,agents,context,ml
