Agentic AI Solution Engineer

Booz Allen HamiltonAtlanta, GA
13d

About The Position

Agentic AI Solution Engineer Key Role: Design and build robust knowledge frameworks enabling AI systems to dynamically interact with structured and unstructured public health data, facilitating 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 to facilitate multi-modal data integration, partnering closely with data engineers on data pipeline coordination. Lead performance optimization of retrieval processes for public health use cases and 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

Nice To Haves

  • 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
  • Possession of excellent communication skills, including facilitating collaboration between technical teams, public health experts, and stakeholders

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 to facilitate multi-modal data integration
  • Partner closely with data engineers on data pipeline coordination
  • 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

Benefits

  • health
  • life
  • disability
  • financial
  • retirement benefits
  • paid leave
  • professional development
  • tuition assistance
  • work-life programs
  • dependent care
  • recognition awards program
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