AI Engineer

Accylerate, LLC.; Herndon (VA); On-site; USD 150,000 - 210,000; Full time

Job summary

Accylerate, LLC is seeking an AI Engineer with a Top Secret clearance to design and implement advanced AI/ML architectures, cloud data pipelines, and governance frameworks within DoD/IC contexts. The role focuses on agentic AI, RAG architectures, vector databases, model monitoring, and secure API development, collaborating with enterprise teams to integrate AI into enterprise platforms.

Candidates should have 3+ years' experience, a CS/engineering/data science degree, and certifications such as

Qualifications

• Active TS security clearance with SCI eligibility.
• Degree in CS/Engineering/Data Science; master's preferred.
• 3+ years in AI/ML engineering or solution development.
• Experience with AWS, Azure, or Google Cloud.
• Proficiency in Python and ML frameworks; API development.
• Understanding AI governance and model lifecycle concepts.
• DoD 8140 certification.
• Ability to obtain/maintain TS clearance.

Responsibilities

• Design and implement AI/ML architectures and cloud data pipelines.
• Develop governance frameworks and lifecycle management capabilities.
• Create agentic AI architectures and multi-agent orchestration.
• Develop RAG architectures and vector database integrations.
• Support explainability, bias detection, monitoring, and drift management.
• Collaborate with enterprise architects to integrate AI into platforms.
• Assist architecture governance reviews and assessments.
• Document AI architecture designs and guidance.

Skills

Active TS clearance

SCI eligibility

Python development

AI/ML engineering

Cloud platforms (AWS/Azure/GCP)

AI governance & lifecycle

DoD 8140 certification

Agentic AI architectures

Vector databases

Education

Bachelor's degree in CS/Engineering/Data Science

Master's degree preferred

Tools

TensorFlow/PyTorch

API development

Vector databases

ML monitoring tools

Job description

Ideal Candidate Profile:

Seeking an AI Engineer with experience in AI/ML engineering, Python development, cloud-based data pipelines, and machine learning frameworks. Must hold an active Top Secret (TS) security clearance and DoD 8140 certification, with knowledge of AI model governance, lifecycle management, agentic AI, RAG architectures, vector databases, and AI monitoring, preferably in DoD or Intelligence Community environments.

Job Duties & Responsibilities

• 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.

Required Skills

• 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.

Preferred Skills

• 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.