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Data Scientist Specialist

United States, McLean · Job Posted December 19, 2025
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Job Description

We are seeking a highly experienced Data Scientist Specialist with deep expertise in Generative AI (GenAI) to lead the design and development of advanced AI Agents, agentic workflows, and GenAI applications that solve complex enterprise challenges.

Job Responsibility

  • Architect and implement GenAI systems: Build scalable AI agents, agentic workflows, and GenAI applications for diverse business use cases
  • Model development & optimization: Fine-tune and optimize lightweight LLMs
  • evaluate and adapt models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives
  • RAG & GraphRAG architectures: Design and deploy Retrieval-Augmented Generation (RAG) and GraphRAG systems using vector databases and enterprise knowledge bases
  • Enterprise data curation: Curate and prepare enterprise data using connectors integrated with AWS Bedrock Knowledge Bases and/or Elasticsearch
  • Agent interoperability: Implement solutions leveraging Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication patterns
  • Experimentation & ML platforms: Build and maintain Jupyter-based notebooks using SageMaker, MLFlow, or Kubeflow on Kubernetes (EKS)
  • Cross-functional collaboration: Work with UI engineers, microservices teams, designers, and data engineers to deliver full-stack GenAI experiences
  • Enterprise integration: Integrate GenAI solutions with enterprise platforms via APIs and standardized GenAI architectural patterns
  • Evaluation & safety: Establish evaluation frameworks, bias mitigation strategies, safety protocols, and guardrails for production deployment
  • Data ingestion & preprocessing: Build ingestion pipelines that extract, chunk, enrich, and anonymize data from PDFs, video, and audio using semantic chunking and privacy controls
  • Multimodal ETL orchestration: Orchestrate multimodal pipelines using Apache Spark, PySpark, or similar frameworks for automated ETL/ELT workflows
  • Embeddings & vector search: Implement embedding-driven architectures and integrate with vector stores (AWS Knowledge Bases, Elasticsearch, MongoDB Atlas) to support RAG and agentic systems

Requirements

  • Bachelor’s or Master’s degree in AI, Data Science, Computer Science, or related field
  • Extensive experience in AI/ML, including 3+ years in applied GenAI or LLM-based solutions
  • Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases, and multi-modal models
  • Proven experience with AWS cloud-native AI development (SageMaker, Bedrock, MLFlow/Kubeflow on EKS)
  • Strong programming skills in Python and ML/LLM libraries (Transformers, LangChain, etc.)
  • Strong understanding of GenAI system patterns, agentic architectures, evaluation frameworks, and guardrails
  • Demonstrated success working in cross-functional, agile teams
  • GitHub code repository link required for candidate evaluation

Nice to have

  • Published research, conference contributions, or patents in AI/ML/LLM domains
  • Experience with enterprise AI governance, responsible AI, and ethical deployment frameworks
  • Familiarity with MLOps, CI/CD pipelines, and scalable inference APIs

What we offer

  • medical
  • dental
  • vision
  • life
  • disability
  • other insurance plans
  • ESPP (employee stock purchase program)
  • 401K program with company match after 12 months
  • HSA (Health Savings Account on the HDHP plan)
  • SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions
  • corporate discount savings program
  • other discounts
  • on-demand training program
  • access to certification prep and a library of technical and leadership courses/books/seminars after 6+ months tenure
  • certification discounts and other perks to associations that include CompTIA and IIBA
  • dedicated customer service team
  • certified Career Coach

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