AI Data Scientist Specialist

Job Title: AI Data Scientist Specialist

Location:
McLean, Virginia 22102 (Fully 5 days onsite)

Duration: 06 Months Contract

We are seeking a highly experienced Data Scientist Specialist 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. The ideal candidate will have 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.

This role involves working collaboratively with full‑stack developers, UX designers, product managers, and data engineers to shape and implement enterprise‑grade Gen AI solutions.

• 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 Sage Maker 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 and 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 Knowledge Base/Elastic/Mongo Atlas) to support RAG architectures.

• MS/PhD in AI/Data Science.
• 10 years of experience in AI/ML, with 3 years in applied GenAI or LLM‑based solutions.
• Deep expertise in prompt engineering, fine‑tuning, RAG, Graph
  
  RAG, vector databases (e.g., AWS Knowledge Base / Elastic), and multi‑modal models.
• Proven experience with cloud‑native AI development (AWS Sage Maker, Bedrock, MLFlow on EKS).
• Strong programming skills in Python and ML libraries (Transformers, Lang Chain, 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.

• 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.

Pay Range: $90‑$100/hr

The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full‑time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work.