Description

Design and build enterprise-grade LLM and RAG-based solutions, leading hands-on development and optimizing real-world AI applications.

This role is hybrid.

Responsibilities

• Design and implement LLM-powered applications using RAG, embeddings, and agentic AI.
• Build scalable end-to-end AI architectures that integrate enterprise data securely.
• Optimize LLM performance metrics including RPM, TPM, latency, and cost.
• Ensure data security and masking for sensitive information within AI pipelines.
• Lead development using Python and APIs while translating business requirements into technical solutions.

Required Skills

• Strong experience in Generative AI, LLMs, and RAG implementation.
• Expertise in prompt engineering (temperature, top-p) and vector databases.
• API integrations with OpenAI and Azure OpenAI.
• Proficient coding in Python (mandatory).
• Experience with system design and scalable architectures.
• End-to-end LLM + RAG implementation experience.
• Ability to handle hallucinations and retrieval issues.

Preferred Skills

• Experience with MCP and Agentic AI.
• Exposure to the Banking or Financial domain.
• Proficiency in Java and Spring Boot.

Key Skills

Education

Any Graduate