AI/ML Engineer

Build and optimize RAG pipelines, design agentic AI systems, and develop applied AI solutions that integrate with customer backend systems. Implement AI services on Kubernetes and work directly with customers to deliver technical implementations. Required skills: strong experience with LLMs, agent frameworks, Python, vector databases, and containerization.

• Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows
• Design agentic AI systems — including tool calling, orchestration, reasoning loops, and workflow automation
• Develop Applied AI solutions that integrate with customer backend systems, APIs, and data sources
• Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure
• Work directly with customers to deliver high-quality technical implementations, demos, and documentation

• Strong experience with LLMs and agent frameworks such as LangChain, LlamaIndex, or custom-built solutions
• Expertise in Python, vector databases (Elastic, Milvus, Pinecone, etc.), embeddings, and chunking strategies
• Hands-on experience with Kubernetes, Docker, and scalable API deployment
• Ability to understand customer workflows and translate them into actionable technical solutions