Description

You will architect and implement modern AI infrastructure, focusing on Vector Databases and Retrieval-Augmented Generation (RAG) systems.

This role is on-site.

Responsibilities

• Architect end-to-end AI/ML systems and integrate RAG frameworks with Vector Databases.
• Define and deploy AI-powered search and knowledge systems for production use.
• Collaborate with stakeholders on data embedding, indexing, and semantic retrieval strategies.
• Guide the roadmap for Generative AI adoption while ensuring system scalability.
• Deliver production-ready AI solutions independently.

Required Skills

• 10+ years in software architecture and system design.
• 5+ years of hands-on experience in AI/ML.
• Proficiency with Vector Databases such as Pinecone, Milvus, Weaviate, or FAISS.
• Proven expertise in RAG frameworks and LLM integration.
• Strong skills in Python, LangChain, or similar tools.
• Deep knowledge of semantic search, data embedding, and prompt engineering.
• Experience with AWS, Azure, or GCP cloud platforms.
• Stakeholder management experience.

Preferred Skills

• Master’s or Ph.D. in Computer Science, AI/ML, or Data Engineering.
• Experience building enterprise-scale AI search systems.

Key Skills

Education

Master’s/Ph.D. in Computer Science