Senior Specialist, Systems Integration Engineer managing system integration and testing for advanced technologies. Collaborating across multidisciplinary teams on design verification and troubleshooting issues in Ashburn, VA.
About the role
- Designing robust AI knowledge frameworks for dynamic interaction with public health data. Leading performance optimization and ensuring compliance with data privacy standards in health management.
Responsibilities
- Design and build robust knowledge frameworks enabling AI systems to dynamically interact with structured and unstructured public health data
- Facilitate real-time insights and decision-making support
- Leverage knowledge of the design and implementation of base architectures, data modeling for AI agents, Memory and State Management, and construction of RAG Pipeline Design for multi-modal data integration
- Lead performance optimization of retrieval processes for public health use cases
- Define rigorous data quality and curation standards
- Collaborate with AI teams and maintain thorough documentation of data architecture
- Ensure compliance with data privacy standards, anonymization protocols, and ethical guidelines critical to public health data management
Requirements
- 4+ years of experience in data science, solution architecture, or data engineering
- 2+ years of experience with AI, ML, or knowledge-based systems
- Experience in knowledge management, semantic search, and public health information retrieval
- Experience designing knowledge graphs, ontologies, and semantic frameworks, including PEFT, RDF, OWL, or Neo4j
- Experience with vector databases, including Azure AI Search, PostgreSQL PgVector, Pinecone, Weaviate, or PyTorch
- Knowledge of NLP methods and libraries, including spaCy, NLTK, or Hugging Face Transformers
- Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
- Bachelor’s degree
- Experience in analytics to abstract complex public health data into structured, actionable models
- Experience in data-centric AI or ML projects within healthcare, biomedical, or public health sectors
- Experience designing APIs, microservices architecture, including FastAPI or Flask, and caching mechanisms such as Redis
- Knowledge of cloud-based AI data platforms, including AWS Kendra, AWS Bedrock, Azure Cognitive Search, or GCP Vertex AI
- Knowledge of data ethics, privacy standards, and security protocols
- Ability to adopt and implement emerging AI technologies such as LlamaIndex or advanced memory architectures
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
- recognition awards program
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