Location: Chantilly, VA
Security Clearance: Active TS or higher [Required]
Job Type: Full-Time
Target Salary Range*: $150,000 - $206,000
- 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 Technical Targeting Analyst (AI) serves as the principal subject matter expert for AI-enabled targeting methodologies, intelligence-driven data analysis, and advanced analytical integration across complex operational environments. This role applies artificial intelligence, machine learning, cyber intelligence, and large-scale data exploitation techniques to identify and assess high-priority threats and develop actionable intelligence. The SME provides strategic leadership in analytic modernization, data-driven targeting, and cross-domain intelligence integration while ensuring ethical, secure, and effective use of emerging technologies.
Key Responsibilities
Intelligence Analysis and Targeting
- Apply advanced analytical techniques, data exploitation tools, and intelligence collection methodologies to identify and assess high-priority threats.
- Analyze large, complex datasets from multiple intelligence and operational sources.
- Develop actionable intelligence, targeting packages, and executive-level briefings.
AI-Enabled Analytic Modernization
- Apply AI, machine learning, and data-driven analytical frameworks to support targeting and intelligence analysis.
- Provide strategic leadership in analytic modernization and the integration of advanced analytical capabilities.
- Support cross-domain intelligence integration across complex operational environments.
Technical Leadership and Analytical Governance
- Lead complex analytic efforts and advise senior stakeholders.
- Serve as the principal authority for AI-enabled targeting methodologies.
- Ensure ethical, secure, and effective use of emerging technologies.
Qualifications
Education
- Bachelor’s degree required.
Experience
- Minimum of 10 years of experience.
- Experience using advanced analytical techniques, data exploitation tools, and intelligence collection methodologies.
- Experience analyzing large, complex datasets from multiple intelligence and operational sources.
- Experience developing intelligence products, targeting packages, and executive-level briefings.
Skills
- Knowledge of artificial intelligence, machine learning, and data-driven analytical frameworks.
- Strong critical thinking, investigative, and problem-solving skills.
- Ability to lead complex analytic efforts and advise senior stakeholders.
- Technical capabilities supporting an in-house, custom-developed application.
Advanced AI, GenAI, and Multimodel Engineering
- Multimodel and multimodal orchestration involving reasoning, perception, memory, and tool execution.
- Temporal, spatial, geographic, quantitative, and computer vision AI implementation.
- Named entity recognition (NER), contextual entity extraction, and entity resolution.
- Multistep retrieval and structured output generation.
- Complex data parsing and streamlined ingestion.
- Detailed source citation and traceable analytic outputs.
Data Architecture and ETL
- Vector, graph, and multiple database orchestration.
- Automated extract, transform, and load (ETL) pipeline creation, scheduling, and optimization.
- Attribute-based access control (ABAC) at the data layer.
- Data provenance and end‑to‑end lineage tracking.
- Schema-aligned ingestion and normalization of diverse structured and unstructured data.
Enterprise Infrastructure and Cross-Domain Solutions
- Air‑gapped, hybrid, and on‑premises operational environments.
- Container orchestration and distributed systems management using Kubernetes.
- Locally hosted GPU servers and hyperconverged nodes.
- Multitenant cross-domain solutions (CDS).
Application Development and Integration
- UI, backend, and middleware engineering using TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
- Integration of reasoning components, retrieval systems, databases, and AI/GenAI services.
- Use of modern programming languages and frameworks.
Preferred Qualifications
- Master’s degree in Intelligence, Data Science, Cybersecurity, Analytics, or a related field.
- Experience supporting federal, defense, intelligence, law enforcement, or national security missions.
- Expertise in AI/ML model development, data engineering, or advanced analytics platforms.
- Experience with cyber threat intelligence, network analysis, digital forensics, or open-source intelligence (OSINT).
- Knowledge of intelligence tradecraft, operational targeting methodologies, and analytical governance.
- Relevant certifications in intelligence analysis, cybersecurity, data science, cloud technologies, or AI/ML disciplines.