Job Description – Data Scientist (Agentic AI)

Location: San Jose, CA (Hybrid/Onsite)

F2F Interview Must

About the Role

We are seeking an experienced Data Scientist with expertise in Agentic AI, Generative AI, and Machine Learning to design and deploy intelligent AI systems capable of autonomous reasoning, planning, tool usage, and multi-step decision-making. The ideal candidate will have a strong foundation in data science and hands-on experience building AI agents powered by large language models (LLMs) that solve complex business problems at scale.

Key Responsibilities

• Design, develop, and deploy Agentic AI solutions using LLMs and autonomous AI frameworks.
• Build multi-agent systems capable of planning, reasoning, memory management, and tool orchestration.
• Develop predictive models, recommendation systems, and advanced analytics solutions.
• Fine-tune, evaluate, and optimize LLMs for enterprise use cases.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Develop AI workflows that integrate with enterprise applications through APIs and external tools.
• Collaborate with Product, Engineering, and Business teams to identify AI opportunities and deliver production-ready solutions.
• Design evaluation frameworks for AI agents, including reasoning quality, latency, accuracy, and safety.
• Build scalable ML pipelines and support MLOps practices for model deployment and monitoring.
• Stay current with advancements in Agentic AI, Generative AI, and machine learning research.

Required Qualifications

• Bachelor''s or Master''s degree in Computer Science, Data Science, Statistics, Mathematics, AI, or a related field.
• 4+ years of experience in Data Science or Machine Learning.
• 2+ years of hands-on experience with Generative AI and LLM-based applications.
• Strong programming skills in Python and SQL.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience building Agentic AI applications using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar.
• Strong understanding of prompt engineering, function/tool calling, structured outputs, and LLM evaluation.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.
• Familiarity with RAG architectures and embedding models.
• Experience working with OpenAI, Anthropic, Google Gemini, or other enterprise LLM APIs.
• Excellent analytical, communication, and stakeholder management skills.