Quick Overview
Job Description
AI Engineer
Clearance: Top Secret with SCI eligibility
Location: Herndon, VA (Hybrid)
What You’ll Do:
The AI Engineer supports the design, development, and governance of Artificial Intelligence (AI) and Machine Learning (ML) architectures supporting enterprise modernization initiatives. This role contributes to AI architecture development, model governance, data pipeline engineering, and agentic AI capabilities while ensuring alignment with enterprise architecture standards and governance requirements.
Responsibilities will include but are not limited to:
- Support the design and implementation of AI/ML architectures and cloud-based data pipelines.
- Develop AI model governance frameworks, monitoring processes, and lifecycle management capabilities.
- Design and implement agentic AI architectures, including multi-agent orchestration frameworks and autonomous workflow solutions.
- Develop retrieval-augmented generation (RAG) architectures and vector database integrations.
- Support explainability, bias detection, model performance monitoring, and drift management activities.
- Collaborate with enterprise architects and engineering teams to integrate AI technologies into enterprise platforms.
- Support architecture governance reviews and technical assessments.
- Document AI architecture designs, standards, and implementation guidance.
What You’ll Need:
- Active Top Secret (TS) security clearance with SCI eligibility.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field, Master preferred
- 3+ years of experience supporting AI/ML engineering or solution development.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with Python, machine learning frameworks, and API development.
- Understanding of AI governance, model lifecycle management, and data architecture concepts.
- Must be DOW 8140 certified
- Ability to obtain and maintain required Top Secret government security clearance.
Set Yourself Apart With:
- Master’s degree in Computer Science, Engineering, Information Technology, or related discipline.
- Experience supporting DoD or Intelligence Community environments.
- AWS or Azure AI/ML specialty certification
- Experience with large language models (LLMs), RAG, and vector databases.
- Knowledge of MLOps tools and AI observability platforms.
- Familiarity with NIST AI Risk Management Framework and DoD AI guidance.
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