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Principal Data Scientist Agentic AI & Applied Intelligence
Job Description
Principal Data Scientist
•Agentic AI & Applied Intelligence Blupace Raleigh, NC Job Details Contract $55
•$60 an hour 18 hours ago Qualifications AI models Gradient boosting machines Hypothesis testing Design of experiments Testing and evaluation Spark Generative models AI platforms (beyond public GPTs) Computational framework SQL Production systems Spark implementation Machine intelligence Inferential statistics XGBoost Data science Model evaluation Machine learning frameworks Statistical significance testing
Python Generative AI Full Job Description Job Role:
Principal Data Scientist
•
Agentic AI & Applied Intelligence Location:
RELOCATION
to Raleigh NC
•2 days onsite
Type:
6MO
CONTRACT TO HIRE
Hiring:
Bulk Hiring |
One-Round Interview Experience:
10+ years Position Summary We are seeking a highly experienced Principal Data Scientist with 10+ years of experience in Data Science, Machine Learning, and AI systems development, including recent hands-on expertise in Agentic AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and enterprise AI platforms . This role will lead the design and evaluation of intelligent AI systems that combine machine learning, statistical modeling, retrieval systems, reasoning frameworks, and agent orchestration to solve complex business problems. The ideal candidate can operate at both the strategic and technical levels, driving AI innovation while remaining deeply hands-on in experimentation, evaluation, architecture, and production deployment. Key Responsibilities Agentic
AI & LLM
Systems Design and develop multi-agent AI systems using frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, ADK, or custom orchestrators. Build planner-executor architectures, tool-using agents, memory-enabled agents, and agent collaboration workflows. Design agent routing, state management, agent evaluation, and human-in-the-loop workflows. Create enterprise-grade AI assistants, copilot solutions, and decision-support systems. Data Science & Modeling Lead development of predictive models across classification, forecasting, optimization, anomaly detection, recommendation systems, and risk analytics. Design experimentation frameworks including A/B testing, causal inference, uplift modeling, and statistical validation methodologies. Build interpretable machine learning systems and define KPIs that directly align with business outcomes. Develop advanced feature engineering strategies for structured and unstructured enterprise datasets. Retrieval & Knowledge Systems Architect RAG solutions using: Hybrid retrieval Semantic search Knowledge graphs GraphRAG Vector databases Re-ranking architectures Design chunking, embedding, indexing, and retrieval optimization strategies. Develop retrieval evaluation frameworks using Recall@K, Precision@K, MRR, NDCG, and human evaluation. AI Evaluation & Governance Design evaluation frameworks for: Hallucination detection Groundedness Faithfulness Agent reliability Tool-calling accuracy Task completion success Develop golden datasets and benchmark suites. Implement AI governance frameworks supporting model risk management, explainability, compliance, and auditability. Leadership Mentor Data Scientists, Applied Scientists, and ML Engineers. Guide architecture reviews and technical design decisions. Partner with Product, Engineering, Legal, Compliance, and Executive Leadership. Drive AI roadmap development and platform adoption. Required Qualifications Master's or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or related field. 10+ years of experience in Data Science and Machine Learning. 3+ years building production GenAI systems.
Expertise in:
Python SQL PySpark Scikit-Learn XGBoost Deep Learning frameworks Experience with: LangChain LangGraph LlamaIndex RAG Multi-agent architectures Model evaluation frameworks Strong understanding of: Statistics Hypothesis testing Experimental design Causal inference Preferred Qualifications Production experience with GraphRAG. Experience with MCP (Model Context Protocol). Experience with A2A (Agent-to-Agent communication). Publications, patents, or conference speaking experience. Experience in regulated industries such as healthcare, finance, insurance, or legal.
Pay:
$55.00
•$60.00 per hour
Work Location:
In person