Description

You will build and optimize RAG pipelines, agentic AI systems, and applied AI solutions that integrate with customer backend systems and APIs. You will implement these services on Kubernetes or cloud environments and deliver high-quality technical implementations and documentation.

This role is on-site.

Responsibilities

• 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.
• Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure.
• Integrate AI workflows with PLM systems or enterprise knowledge platforms.
• Work directly with customers to deliver technical implementations, demos, and documentation.

Required Skills

• 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.
• 5+ years of experience in AI/ML engineering.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

• Experience integrating with PLM systems or enterprise knowledge platforms.

Key Skills

Education

Bachelor's degree