AI / ML Engineer

Active TS/SCI security clearance required. Benz Technology is unable to sponsor clearances. U.S. citizenship required.

About the Role

You will design, develop, and deploy AI and ML solutions spanning LLM-powered tooling, RAG architectures, and analytics workflows within governed, secure cloud environments. This role covers the full lifecycle from data engineering and model development through production deployment, with direct integration into front-end experiences and automated software analysis systems. You will collaborate closely with customers and engineering teams to build compliant, auditable, and high-impact AI capabilities.

Responsibilities

• Design and implement LLM-powered applications including RAG frameworks, fine-tuned models, and orchestration pipelines
• Develop and maintain data engineering workflows using Python, PySpark, and cloud-native tools
• Deploy and manage containerized AI workloads on Kubernetes and AWS infrastructure including SageMaker and EKS
• Integrate AI capabilities with static analysis, automated testing, and software certification systems
• Build front-end analytics experiences using React and AWS Amplify to surface and summarize data for end users
• Implement and maintain AI/ML governance frameworks ensuring models are compliant, versioned, and auditable
• Contribute to Agile development cycles using Git, Jira, and Confluence with consistent CI/CD practices

Required Qualifications

• Python development and data engineering
• LLM integration, fine-tuning, and RAG framework design
• Relational and vector database design
• PySpark and Jupyter Notebooks
• Kubernetes and Docker
• AWS SageMaker and AWS EKS
• AWS Amplify and React
• Elasticsearch Static analysis tooling experience
• Git, GitLab, Jira, and Confluence
• AI/ML governance framework implementation
• Agile development practices

Desired Qualifications

• Rust programming language
• AI coding assistants such as Claude Code or OpenAI Codex
• Hugging Face and model registry tools such as Bailo
• CI/CD pipeline design and tooling
• GMLearn or Container Yard platform experience
• Query Time Analytics Experience
• Deploying AI systems within secure enclaves or classified networks
• Familiarity with customer corporate tools and internal data repositories