Description

Architect and deliver end-to-end LLM-powered applications and agentic workflows.

This role is on-site.

Responsibilities

• Design and implement RAG pipelines over enterprise data using embeddings and vector databases.
• Build multi-step, tool-using agents with planning, execution, and memory capabilities.
• Integrate AI systems with APIs, backend services, and cloud platforms.
• Establish evaluation, reliability, and performance strategies for accuracy, latency, and cost.

Required Skills

• Strong programming experience in Python and Javascript.
• Experience with LangChain, LangGraph, and agentic frameworks.
• Deep understanding of RAG architectures, embeddings, and vector databases.
• Ability to build production-grade backend systems and deploy AI applications.
• Experience with LLMs, including prompt engineering and orchestration.
• 5+ years of professional experience.

Preferred Skills

• Experience with AutoGen.

Key Skills

Education

Any Gradute