Senior Data Scientist - GenAI / RAG

AITA Consulting Services Inc.

Houston, TX, United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

7 years minimum

Compensation

$75,000.0 - $90,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Data Infrastructure Graph Database Monitoring of Systems Python (Programming Language) Machine Learning Tensorflow Standard Sql

+16 more

Feature Engineering Pytorch Retrieval-Augmented Generation Large Language Models Snowflake Multi-Agent Systems Random Forest Apache Spark Deep Learning Model Validation Build Management AI Platforms Xgboost Machine Learning Operations Virtual Agents Databricks

Job description

Build and deploy RAG (Retrieval-Augmented Generation) systems & AI chat interfaces
Work closely with client data science teams (ML/DL ecosystems)
Develop GenAI-based enterprise knowledge solutions
Collaborate directly with stakeholders and customers

Tech Environment

AWS ecosystem
Snowflake (data platform)

Requirements

Focus: We need candidates with real hands-on experience in Agentic AI and Traditional Data Science, not candidates who have only recently started exploring GenAI/LLMs. Continuous production implementation experience is preferred. What the Hiring Team is Looking For

Traditional Data Scientists who have evolved into GenAI/Agentic AI solutions.
Candidates who can discuss end-to-end problem solving, feature engineering, predictive analytics, model selection, and solution design.
Hands-on experience designing and implementing RAG, LLM, and Agentic AI solutions.
Strong understanding of business use cases and ability to interact with customers and stakeholders.
Ability to explain architecture decisions, technical trade-offs, and implementation approaches.

Mandatory Skills

Strong Data Science background
Strong Machine Learning implementation experience
Hands-on LLM & RAG architecture and implementation
Experience with Agentic AI concepts and workflows
Strong client-facing / consulting and stakeholder communication skills
Exposure to Deep Learning concepts and implementations
Experience with cloud AI platforms such as AWS Bedrock, Azure OpenAI, or Vertex AI, * Strong hands-on experience in Agentic AI and Multi-Agent Systems
Experience with LangGraph, LangChain, MCP (Model Context Protocol), tool calling, agent orchestration
Strong RAG implementation experience including Vector Databases, Hybrid Retrieval, Reranking, Knowledge Graphs
Hands-on experience with AWS Bedrock and enterprise GenAI solutions
Strong Python and SQL skills
Solid Traditional Data Science / Machine Learning background:
Classification
Regression
Forecasting
Anomaly Detection
Feature Engineering
Model Evaluation
Experience with XGBoost, CatBoost, Random Forest, Deep Learning frameworks (PyTorch/TensorFlow)
Experience designing and deploying production AI/ML systems
Understanding of MLOps / LLMOps, model monitoring, evaluation, observability, and retraining pipelines
Ability to translate business problems into ML or Agentic AI solutions
Experience with LLM Evaluation, Hallucination Detection, Groundedness and Retrieval Quality metrics
Exposure to Databricks, Spark, Vector Databases, APIs, Cloud Platforms (AWS preferred)

About the company

ABOUT POWER FACTORS Power Factors is a leading software and solutions provider supporting the next generation of clean energy through Unity, one of the most comprehensive and wid…