Artificial Intelligence Architect

MANTECH•Chantilly, VA

2d•$114,600 - $190,200•Onsite

About The Position

MANTECH seeks a motivated, career- and customer-oriented AI Systems Architect / Senior AI Developer to join its team in Chantilly, Virginia. The role bridges high-level system architecture with hands-on software development, translating complex mission objectives into scalable, secure, and performant AI/ML systems for air-gapped and high-security environments. The position supports government intelligence agencies and requires an active Top Secret/SCI with Polygraph clearance before starting. The role covers end-to-end AI/ML architecture and implementation, including MLOps, data integration, LLMs, computer vision, NLP, predictive analytics, REST APIs, microservices, data pipelines, RAG architectures, vector databases, and agentic workflows. The architect also serves as the primary AI/ML technical subject matter expert for government stakeholders and program leadership, while mentoring developers and data scientists. The projected compensation range is $114,600.00–$190,200.00. Final compensation may depend on factors including contract wage determination, relevant experience, skills, location, education, certifications, and federal contract labor categories. Benefits may include health and life insurance, paid time off, holiday pay, short- and long-term disability, retirement and savings, learning and development, wellness programs, and optional benefit elections, depending on the position.

Requirements

Bachelor’s degree in computer science, computer engineering, software engineering, or a closely related technical field; six additional years of software engineering experience may substitute for a bachelor’s degree.
At least five years of progressive professional software engineering experience, including at least two years building, deploying, and maintaining AI/ML applications in production.
Proficiency in Python and hands-on experience with AI/ML toolkits such as PyTorch, TensorFlow, Hugging Face Transformers, Scikit-Learn, or OpenCV.
Experience implementing GenAI solutions, prompt engineering, fine-tuning techniques such as LoRA/QLoRA, or RAG pipeline architectures.
Experience deploying models using Docker, Kubernetes, MLOps frameworks, or vector databases.
Knowledge of or experience with Risk Management Framework standards and ICD 503 guidelines in air-gapped environments.
Active Security+ CE or higher certification for privileged user access, or ability to obtain it within 60 days of hire.
Active Top Secret/SCI with Polygraph clearance before starting.
Ability to remain stationary 50% of the time.
Ability to occasionally move around the office to access file cabinets, office machinery, and similar items.
Ability to communicate frequently with coworkers, management, and customers, including delivering presentations and exchanging accurate information.

Nice To Haves

Master’s degree in computer science, data science, or artificial intelligence.
Experience integrating AI capabilities with Intelligence Community data standards, networks, and classified cloud infrastructures such as AWS C2S, SC2S, or Azure Secret/Top Secret.
Familiarity with hardware acceleration techniques such as NVIDIA CUDA, TensorRT, model quantization/pruning, and adversarial machine learning or AI safety.
Relevant industry certifications such as AWS Certified Machine Learning – Specialty, Certified Kubernetes Administrator (CKA), or CISSP.
Self-starter with strong people skills, able to work across teams, organize meetings or boards, and drive organizational change.

Responsibilities

Architect end-to-end AI/ML pipelines, MLOps frameworks, and data integration platforms for high-security, classified environments.
Design robust, modular software architectures for LLMs, computer vision, NLP, and predictive analytics.
Build scalable REST APIs, microservices, and ETL/data ingestion pipelines for real-time and batch inferencing.
Implement RAG architectures, vector databases, and agentic workflows for unstructured, multi-source data.
Establish secure CI/CD pipelines and automated testing protocols for model validation, drift detection, and deployment in isolated environments.
Serve as the primary technical subject matter expert on AI/ML capabilities for government stakeholders and program leadership.
Mentor mid-level developers and data scientists in secure software design, model optimization, and scalable pipeline development.