AI Solutions Engineer
Core
Design, deploy, and operate reliable infrastructure for ML, LLM, and RAG workloads to support vehicle design, manufacture, flight test, and business teams.
Role type
Senior IC MLOps and AI infrastructure engineer
Builds
Production ML/LLM/RAG systems, APIs, plugins, SDKs, and developer tools for internal users
Domain
Aerospace engineering + Cloud-native AI infrastructure
Deliverable
production ML models
Required skills
Python, Rust, C, MATLAB, AWS, Docker, Kubernetes, Dagster, CI/CD, API development, observability, CLI scripting
Preferred skills
MLOps, LLM optimization, vector databases (Qdrant), Hugging Face, OpenWebUI, frontend integration (Streamlit, NGINX), aerospace workflows
Technologies
AWS (EC2, Lambda, ECS, EKS, S3, CloudWatch), Qdrant, PostgreSQL, MongoDB, Jenkins, GitLab, Bamboo, Streamlit, NGINX
Responsibilities
Design and operate ML/LLM/RAG infrastructure; host and monitor RAG systems; serve as MLOps subject matter expert; integrate COTS and third-party AI tools; develop APIs and reusable integrations; collaborate on team-specific AI workflows
Seniority
Senior, hands-on IC