Data Scientist Specialist

McLean, VA, US • Posted 9 days ago • Updated 4 hours ago

Contract Independent

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Job Details

Skills

with 3+ years in applied GenAI or LLM-based solutions. * Deep expertise in prompt engineering
fine-tuning
RAG
GraphRAG
vector databases (e.g.
AWS KnowledgeBase / Elastic)
and multi-modal models. * Proven experience with cloud-native AI development (AWS SageMaker
Bedrock
MLFlow on EKS). * Strong programming skills in Python and ML libraries (Transformers
LangChain
etc.). * Deep understanding of Gen AI system patterns and architectural best practices
**Required Qualifications:** * BA or MS in AI/Data Science * experience in AI/ML
Evaluation Frameworks * Demonstrated ability to work in cross-functional agile teams. * Need Github Code Repository Link for each candidate. Please thoroughly vet the candidates. --- **Preferred Qualifications:** * Published contributions or paten

Summary

Job Title: Data Scientist Specialist

Location: McLean, VA (Onsite)

Duration: 5 to 6 Months

NOTE:

Locals Only
Must be available for in-person interview

Job Description:

We are seeking a highly experienced **Principal Gen AI Scientist** with a strong focus on **Generative AI (GenAI)** to lead the design and development of cutting-edge AI Agents, Agentic Workflows and Gen AI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, Gen AI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands-on Gen AI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers and data engineers to shape and implement enterprise-grade Gen AI solutions.

Must Have Qualifications: Must have hands on experience with machine learning transitioned into GenAI. Rag, Python- Jupyter, other Software knowledge, using agents in workflows, strong understanding of data. Preferred: Built AI agent, MCP, A2A, Graph Rag, deployed Gen AI applications to production.

Key Responsibilities:

Architect and implement scalable AI Agents, Agentic Workflows and GenAI applications to address diverse and complex business use cases.
Develop, fine-tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
Curate enterprise data using connectors integrated with AWS Bedrock's Knowledge Base/Elastic
Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.
Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS).
Collaborate with cross-functional teams of UI and microservice engineers, designers, and data engineers to build full-stack Gen AI experiences.
Integrate GenAI solutions with enterprise platforms via API-based methods and GenAI standardized patterns.
Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production-ready deployment.
Design & build robust ingestion pipelines that extract, chunk, enrich, and anonymize data from PDFs, video, and audio sources for use in LLM-powered workflows-leveraging best practices like semantic chunking and privacy controls
Orchestrate multimodal pipelines** using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows appropriate for unstructured media
Implement embeddings drives-map media content to vector representations using embedding models, and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) to support RAG architectures

Required Qualifications:

BA or MS in AI/Data Science
experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions.
Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases (e.g., AWS KnowledgeBase / Elastic), and multi-modal models.
Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).
Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks
Demonstrated ability to work in cross-functional agile teams.
Need Github Code Repository Link for each candidate. Please thoroughly vet the candidates.

Preferred Qualifications:

Published contributions or patents in AI/ML/LLM domains.
Hands-on experience with enterprise AI governance and ethical deployment frameworks.
Familiarity with CI/CD practices for ML Ops and scalable inference APIs.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90806069
Position Id: 2026-12450
Posted 9 days ago

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Data Scientist Specialist

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