AI Data Engineer (Senior)

Location: Chantilly, VA. Security Clearance: Active TS or higher (Required). Job Type: Full-Time.

Pay

Target Salary Range: $150,000 – $170,000 (depending on education, experience, certifications, and position-specific requirements).

Schedule

Full-Time.

About the role

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.

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.

Requirements

Education

• Bachelor’s degree (Required).

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).

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.