Senior Data Scientist – GenAI/RAG

Tasks

• Architect, build and deploy agentic workflows using LangGraph, LangChain, MCP, tool calling, dynamic routing and multi-agent coordination.
• Design and implement end-to-end RAG architectures with vector databases, hybrid search, cross-encoder reranking and knowledge graphs.
• Deploy and scale GenAI applications using AWS Bedrock (or Azure OpenAI / Google Vertex AI) with CI/CD, monitoring and LLMOps practices.
• Build, optimize and validate models for classification, regression, time-series forecasting, anomaly detection and feature engineering (XGBoost, LightGBM, CatBoost).
• Translate business problems into scalable AI/ML architectures and communicate technical trade-offs, governance and evaluation metrics to stakeholders.

Requirements

• 5–7+ Years
• Recent hands-on production GenAI/LLM experience and strong Machine Learning fundamentals.
• Proven experience shipping end-to-end AI/ML and Agentic systems into commercial or enterprise production.
• 12+ months of recent, hands-on GenAI/LLM experience.
• Strong traditional ML/DS foundation and applied experience.
• Hands-on AWS Bedrock (or Azure OpenAI / Google Vertex AI) experience.
• Excellent communication and stakeholder management skills.
• Willingness to attend an in-person final interview at our Santa Clara, CA facility (all travel and lodging expenses covered).
• Preferred: Domain experience in Utilities, Grid operations, Energy or Oil & Gas.
• Preferred: Hands-on experience with Databricks or Snowflake.

Benefits

• Relocation assistance provided.
• All travel and lodging expenses covered for the in-person final interview.

How to apply

• Share your updated resume.
• Reach out with your updated resume.

Location

• Santa Clara, CA
• Dallas, TX
• Houston, TX