Enabling real-world AI by solving hard data engineering problems and integrating graph databases, geospatial sources, real-time sensor data, and AI-native formats across cloud and edge environments for Booz Allen
Requirements
- Experience in Python and a compiled language such as Go or C++
- Experience with multiple data storage technologies, including PostgreSQL, MongoDB, and Neo4j databases
- Experience with containerized environments, including Docker and Podman, and orchestration using Kubernetes
- Experience working with cloud infrastructure, including AWS GovCloud
- Experience with integrating APIs and services into modern applications using frameworks like FastAPI, Gin, or Streamlit
- Knowledge of data modeling, indexing, performance tuning, and data security best practices
- Experience with AI/ML model deployment and supporting AI-native infrastructure such as Llama.cpp, Ollama, or vector databases
Responsibilities
- Take ownership of complex data systems, enabling the flow of information from raw collection to intelligent decision tools
- Help architect and build robust, scalable platforms for modern applications that include embedded AI models, multi-modal interfaces, and interactive dashboards for decision-makers
- Guide teams in designing secure, production-grade data infrastructure
- Write code, design workflows, evaluate technologies, and build infrastructure others rely on
- Operationalize data at the speed of mission
- Integrate graph databases, geospatial sources, real-time sensor data, and AI-native formats across cloud and edge environments
- Deploy vector models inside containerized APIs running on AWS GovCloud
Other
- 5+ years of experience as a data engineer, backend developer, or data platform engineer
- Secret clearance
- Bachelor’s degree in a Computer Science or Engineering field
- Experience mentoring junior engineers or leading small technical teams
- TS/SCI clearance (nice to have)
