Senior Data Scientist - GenAI, RAG

We are looking for a Senior Data Scientist with strong hands-on experience across Traditional Machine Learning, Generative AI, LLMs, RAG, and Agentic AI. The ideal candidate will have 5–7 years of relevant experience, recent and continuous hands-on GenAI experience, and a proven track record of deploying AI/ML solutions into production environments. Strong client-facing communication and consulting experience are essential, as the candidate will need to explain technical architecture, decisions, and trade-offs to both technical and non-technical stakeholders. Position: Senior Data Scientist Location: Houston, TX Job Type: Full-Time Interview: In-person interview required at the Santa Clara, CA office Relocation: Relocation assistance is available for qualified candidates Work Authorization: / / H-1B Transfer Must-Have Skills & Experience 5–7 years of relevant Data Science / Machine Learning experience. Strong traditional Machine Learning/Data Science background, including: Classification Regression Forecasting Anomaly detection Feature engineering Model evaluation and optimization 12+ months of continuous and recent hands-on GenAI/LLM experience. Strong production experience with Agentic AI, including: LangGraph LangChain MCP Tool calling Agent orchestration Hands-on production Agentic AI experience is mandatory — candidates whose experience is limited to POCs, hackathons, certifications, or experimentation will not be considered. Strong depth in RAG implementations, including: Vector databases Hybrid retrieval Reranking Knowledge graphs Hands-on experience with AWS Bedrock. Azure OpenAI or Google Vertex AI can be considered as alternatives, but candidates must have meaningful enterprise GenAI cloud experience. Proven experience deploying and supporting AI/ML systems in production. Strong understanding of LLM application architecture and enterprise AI implementation. Excellent client-facing and consulting communication skills. Ability to explain architecture decisions, technical trade-offs, and AI/ML solutions to non-technical stakeholders. Willingness and ability to attend an in-person interview in Santa Clara, CA. Nice-to-Have Skills Experience in the Energy / Utilities / Oil & Gas / Natural Resources domain. Experience with Databricks and/or Snowflake. Experience with ML frameworks such as XGBoost or CatBoost. Experience with LLMOps, AI evaluation frameworks, and GenAI observability/evaluation tooling. Experience working with enterprise products and customer-facing consulting engagements.