TS/SCI Cleared AI/ML Engineer — LLMs, RAG & Cloud

Benz Technology; Fort Meade (MD); On-site; USD 120,000 - 180,000; Full time

Job summary

Benz Technology is seeking an experienced AI/ML Solutions Engineer to design, develop, and deploy LLM-powered tooling and analytics within governed cloud environments. You will own end-to-end from data engineering to production, integrating AI into front-end experiences and software analysis systems.

Responsibilities span designing RAG frameworks, data pipelines, and containerized workloads on AWS and Kubernetes, with strong emphasis on governance, auditable deployments, and Agile collaboration

Qualifications

• Experience designing and deploying LLM-powered applications.
• Strong data engineering and Python development skills.
• Familiarity with RAG architectures and model orchestration.
• Hands-on experience with cloud-native tooling (AWS, Kubernetes).
• Knowledge of AI governance and auditable deployments.

Responsibilities

• Design and implement LLM-powered applications and RAG frameworks.
• Develop data engineering workflows using Python and PySpark.
• Deploy containerized AI workloads on Kubernetes and AWS (SageMaker, EKS).
• Integrate AI capabilities with static analysis and automated testing systems.
• Build front-end analytics experiences using React and AWS Amplify.
• Maintain AI/ML governance, versioning, and auditable processes.
• Collaborate with customers and engineering teams using Agile practices.

Skills

Python development

Data engineering

LLM integration

RAG framework design

Relational databases

Vector databases

PySpark

Kubernetes

Docker

AWS SageMaker

AWS EKS

AWS Amplify

React

Elasticsearch

Git

GitLab

Jira

Confluence

AI governance

Agile

Tools

SageMaker

EKS

Kubernetes

Docker

GitLab

Jira

Confluence

React

AWS Amplify

Job description

Benz Technology is seeking an experienced AI/ML Solutions Engineer to design, develop, and deploy LLM-powered tooling and analytics within governed cloud environments. You will own end-to-end from data engineering to production, integrating AI into front-end experiences and software analysis systems.

Responsibilities span designing RAG frameworks, data pipelines, and containerized workloads on AWS and Kubernetes, with strong emphasis on governance, auditable deployments, and Agile collaboration