26-1136: AI Engineer 3 - Herndon, VA
About The Position
Navitas is seeking an experienced AI Engineer to support enterprise AI/ML architecture initiatives, governance frameworks, and agentic AI capabilities across federal modernization programs. The role contributes to the design, implementation, and governance of AI-enabled solutions, including enterprise architecture baselines, solution architecture, cloud-based AI platforms, and compliance-driven AI deployment strategies. The position helps establish scalable and secure AI ecosystems aligned with agency architecture standards, governance requirements, and emerging federal AI policies. The AI Engineer works with architects, data engineers, cybersecurity teams, and business stakeholders to support enterprise AI adoption and operationalization. The role also supports responsible AI practices, cybersecurity alignment, governance reviews, and the creation of architecture and compliance documentation.
Requirements
- Active Top Secret (TS) security clearance with SCI eligibility.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- 5+ years of experience supporting AI/ML engineering, data engineering, cloud architecture, software engineering, or related technical disciplines.
- Experience supporting AI/ML solution development within cloud environments.
- Experience working with machine learning frameworks, model lifecycle management, and data pipeline architectures.
- Familiarity with enterprise architecture principles, solution architecture methodologies, and system integration practices.
- Must be DOW 8140 certified.
- Ability to obtain and maintain the required Top Secret government security clearance.
Nice To Haves
- Master’s degree in Computer Science, Engineering, Information Technology, or a related discipline.
- Experience supporting AI governance, responsible AI practices, or compliance-driven technology implementations.
- Experience with AI/ML platforms and services such as Azure AI, Azure Machine Learning, Amazon SageMaker, OpenAI services, or comparable platforms.
- Knowledge of generative AI and large language model (LLM) technologies.
- Experience with agentic AI architectures, retrieval-augmented generation (RAG), model evaluation techniques, and prompt engineering.
- Experience with Python, data engineering frameworks, API integration, and automation tools.
- Knowledge of cloud-native architecture and deployment patterns across AWS and Azure environments.
- Knowledge of enterprise architecture frameworks and governance methodologies.
- Experience with AI security, model monitoring, and compliance reporting.
- AWS Certified Machine Learning Specialty.
- AWS Certified AI Practitioner.
- Microsoft Azure AI Engineer Associate.
- Microsoft Azure Data Scientist Associate.
- Other industry-recognized AI/ML or cloud architecture certifications.
Responsibilities
- Support AI/ML architecture design and engineering across enterprise architecture and modernization initiatives.
- Assist in developing and maintaining enterprise AI architecture baselines, target-state architectures, and transition roadmaps.
- Contribute to solution architecture for AI-enabled systems, integrating cloud-native services and advanced analytics platforms.
- Support the development and maintenance of AI model governance frameworks, including model lifecycle management, risk assessments, and compliance monitoring.
- Assist in designing scalable data pipeline architectures for AI/ML training, inference, monitoring, and continuous improvement.
- Support development of agentic AI systems, including autonomous workflow orchestration, multi-agent architectures, and human-in-the-loop governance mechanisms.
- Assist in establishing prompt engineering standards, prompt governance processes, and evaluation methodologies for generative AI solutions.
- Contribute to AI model fine-tuning pipeline architectures and optimization strategies using cloud-based AI/ML services.
- Produce AI governance artifacts, including model risk scorecards, architecture decision records, agentic system boundary definitions, and deployment documentation.
- Support automated compliance reporting, AI inventory management, and governance dashboards for agency AI initiatives.
- Assist with architecture governance reviews and ensure AI solutions align with enterprise architecture standards, cybersecurity requirements, and responsible AI principles.
- Collaborate with architects, data engineers, cybersecurity teams, and business stakeholders to support enterprise AI adoption and operationalization.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
