Junior AI Engineer
A technology-focused role developing and deploying GenAI and applied AI solutions while supporting secure, high-performance computing infrastructure in hybrid-cloud and air-gapped environments.
Responsibilities
- Design and implement end-to-end architectures for LLM-based systems and AI agents
- Develop and maintain ETL and RAG data processing pipelines
- Integrate AI pipelines with enterprise systems
- Deploy AI solutions in hybrid-cloud and air-gapped environments
- Manage Kubernetes environments, including RKE2
- Allocate GPU resources for production deployments
- Support advanced computing infrastructure across data center, networking, and security environments
- Connect business needs with technological capabilities
Requirements
- At least 2 years of experience in software development, DevOps, systems infrastructure, or solution architecture
- Hands-on experience with dedicated NVIDIA GPU servers such as DGX or HGX
- Knowledge of infrastructure requirements for GPU-based systems
- Familiarity with resiliency standards, tier levels, and high-availability design
- Practical experience developing and implementing applied AI or GenAI solutions
- Strong systems-thinking skills
- Ability to lead cross-functional initiatives
- Commitment to technological excellence, information security, and stringent compliance standards
Nice to have
- Disaster recovery experience
- Knowledge of AI risks such as prompt injection and data leakage
- Python proficiency
- TypeScript, C#/.NET, or PowerShell experience
- Experience with LangChain, LangGraph, or similar agentic frameworks
- Experience with Qdrant, Pinecone, or other vector databases
- Kubernetes or RKE2 administration in secure environments