Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*: $135,000 - $150,000
*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary
Position Overview
The AI Data Engineer (Senior) supports advanced visual analytic applications by building data pipelines, designing large relational databases, and enabling high-performance analysis across structured and semi-structured data. This role helps streamline processes, improve system performance, strengthen secure data practices, mentor junior team members, and contribute to cross-team technical standards.
The position also supports advanced AI and GenAI capabilities, complex data architecture and ETL, enterprise infrastructure, cross-domain environments, and application development and integration across secure, multi-enclave environments.
Key Responsibilities
Data Engineering and Analytics
- Develop data-processing workflows and analytics for desktop- and web-based visual analytic tools.
- Support large-scale relational data analysis using visualization and high-performance computing.
- Build secure data-ingestion pipelines using open-source, COTS, and GOTS technologies.
- Design and optimize enterprise relational databases and establish standards for operations and security.
- Integrate new data systems with existing data warehouses and improve performance and functionality.
- Contribute to system optimization, secure posture improvements, and cross-team technical standards.
AI and GenAI Engineering
- Support advanced AI, GenAI, and multi-model engineering capabilities.
- Implement multi-model and multi-modality orchestration across reasoning, perception, memory, and tool-execution components.
- Support temporal, spatial, geographic, quantitative, and computer-vision AI implementations.
- Implement Named Entity Recognition, contextual entity extraction, and entity resolution.
- Support multi-step retrieval and structured-output generation.
- Perform complex data parsing and streamlined ingestion.
- Support deep source citation and traceable analytic outputs.
Data Architecture and ETL
- Support vector, graph, and multi-database orchestration.
- Develop, schedule, and optimize automated ETL pipelines.
- Implement Attribute-Based Access Control at the data layer.
- Support provenance and end-to-end data lineage tracking.
- Perform schema-aligned ingestion and normalization of diverse structured and unstructured data.
Enterprise Infrastructure and Cross-Domain Solutions
- Support air-gapped, hybrid, and on-premises operational environments.
- Support container orchestration and distributed systems management using Kubernetes.
- Support locally hosted GPU servers and hyperconverged nodes.
- Support multi-tenant Cross-Domain Solutions.
Application Development and Integration
- Support UI, backend, and middleware engineering using technologies such as TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
- Integrate reasoning components, retrieval systems, databases, and AI/GenAI services.
- Apply modern programming languages and frameworks to application development and integration.
Technical Leadership
- Mentor junior team members.
- Contribute to cross-team engineering standards and technical best practices.
- Support improvements to system performance, security, and overall platform functionality.
Qualifications
Education
Experience
- Minimum 8 years of relevant experience. [Required]
- 8+ years of experience in data engineering, database design, or related fields. [Required]
- Experience working with structured and semi-structured data and visualization technologies. [Required]
- Familiarity with high-performance computing and mixed-technology environments. [Required]
- Experience improving data workflows, performance, and security. [Required]
Skills
- Strong relational database design skills. [Required]
- Strong SQL skills. [Required]
- Strong ETL/ELT processing skills. [Required]
- Strong analytical, communication, and collaboration skills. [Required]
Preferred Qualifications
- Experience supporting federal or secure, multi-enclave environments.
- Background with advanced visualization platforms or high-volume data processing.
- Knowledge of data modeling, data warehousing, and performance tuning.
