Data Scientist

💼 Data Scientist Specialist – Principal GenAI Scientist (Consultant) 📍 McLean, VA | Full-Time Onsite (M–F) | W2 Contract Only ⏳ Contract | 2 Open Positions | Potential Long-Term Position Summary: Our financial client is seeking a highly experienced Principal GenAI Scientist with deep expertise in Generative AI, AI Agents, and Agentic Workflows to design and implement cutting-edge enterprise-grade GenAI applications. This role requires strong technical leadership, hands-on development, and collaboration across engineering, product, and data teams. You will work on LLMs, RAG, Graph RAG, MCP, A2A, multimodal AI pipelines, and AWS-based deployments, helping the enterprise shape the next generation of AI-driven business solutions. Key Responsibilities: • Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications for complex business use cases. • Fine-tune and optimize lightweight LLMs; evaluate/adapt models such as Claude (Anthropic), Azure OpenAI, and open-source LLMs. • Design/deploy RAG and Graph RAG systems using vector databases (AWS Knowledge Base, Elastic, Mongo Atlas). • Curate enterprise data using AWS Bedrock connectors and integrate with knowledge bases. • Implement MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication workflows. • Develop Jupyter-based notebooks using SageMaker, MLFlow/Kubeflow on Kubernetes (EKS). • Collaborate with cross-functional teams to build full-stack GenAI solutions with API integrations. • Establish guardrails, validation procedures, and safety protocols for production-ready GenAI deployments. • Design ingestion pipelines for structured/unstructured data (PDF, video, audio) with semantic chunking and privacy controls. • Build multimodal pipelines using Spark/PySpark for automated ETL/ELT workflows. • Implement embeddings pipelines for RAG architectures with vector stores. Required Qualifications: • PhD in AI/Data Science (or equivalent experience). • 10+ years in AI/ML, including 3+ years applied GenAI/LLM solutions. • Hands-on expertise in prompt engineering, fine-tuning, RAG, Graph RAG, vector databases, and multimodal AI models. • Strong Python development with ML libraries (Transformers, LangChain, etc.). • Experience with AWS AI/ML tools (SageMaker, Bedrock, MLFlow on EKS). • Proven track record in GenAI architectural patterns, evaluation frameworks, and bias mitigation. • Ability to collaborate in cross-functional agile teams. • GitHub repository link required for each candidate submission. Preferred Qualifications: • Published contributions or patents in AI/ML/LLM. • Experience with AI governance and ethical deployment frameworks. • Familiarity with CI/CD for ML Ops and scalable inference APIs. Additional Details: • 📌 Location: McLean, VA (Onsite M–F) • 📌 Type: W2 Contract Only