Design, architect, document, and lead the development of AI/ML platform components and agentic AI applications
Implement and optimize cutting-edge AI/ML algorithms and production-quality code, primarily using Python and possibly Go, C, C++, or Rust
Build and deploy container-based applications to platforms like Red Hat OpenShift, public clouds (AWS, GCP, Azure), leveraging CI/CD best practices and MLOps infrastructure
Stay current with advancements in Generative AI and related technologies, conduct root cause analysis
Architect and maintain data pipelines that feed training data, model artifacts, and inference logs into a governed data lake (S3, on prem object store)
Design, implement, and operate a unified MLOps platform that supports both on-premises and commercial cloud platforms hosted Kubernetes clusters
Work closely with research scientists, data scientists, product teams, and stakeholders

Current TS/SCI clearance with Polygraph
Bachelor's degree in Computer Science, Information Systems, Cybersecurity, or related field; or equivalent experience in systems engineering
7+ years of experience as a Platform Engineer, Systems Engineer, DevSecOps Engineer, or Infrastructure Engineer supporting classified DoW or Intelligence Community operations

AI Platform Engineer

Key skills