Cleared Senior AI Engineer — LLM/RAG Architect

Tiber Technologies; Maryland; On-site; USD 140,000 - 180,000; Full time

Job summary

Tiber Technologies seeks a Senior AI Engineer in Maryland to design, develop, and maintain LLM-based AI systems, focusing on retrieval, automation, and vulnerability analysis workflows. You will translate requirements into scalable AI-driven solutions and collaborate with engineers to advance secure, distributed deployments.

The role requires strong Python expertise, production experience with LLMs, and familiarity with data pipelines, vector stores, and CI/CD practices.

Qualifications

• Must be a U.S. citizen.
• Active security clearance with polygraph required.
• Bachelor’s degree in computer science, engineering, or related field.

Responsibilities

• Design, develop, and maintain LLM orchestration frameworks that integrate static analysis tools, retrieval-augmented generation (RAG) systems, and automated testing pipelines
• Develop data ingestion and transformation pipelines to process source code, documentation, and test outputs for AI/ML workflows
• Build and maintain database solutions supporting RAG architectures, including vector stores, metadata management, and audit logging systems
• Collaborate with systems and software engineers to design and deploy AI-enabled tools in secure and distributed environments
• Conduct performance profiling, optimization, and scalability analysis of AI systems
• Support software engineering best practices across the development lifecycle, including testing, deployment, and documentation

Skills

Python

LLM integration

Data pipelines

Vector databases

RAG architectures

Static analysis tools

Agile practices

Education

Bachelor's degree

Tools

Git

Jira

Confluence

Job description

Tiber Technologies seeks a Senior AI Engineer in Maryland to design, develop, and maintain LLM-based AI systems, focusing on retrieval, automation, and vulnerability analysis workflows. You will translate requirements into scalable AI-driven solutions and collaborate with engineers to advance secure, distributed deployments.

The role requires strong Python expertise, production experience with LLMs, and familiarity with data pipelines, vector stores, and CI/CD practices.