Description

Key Skills: Artificial Intelligence, Python, Chatbot, AWS, Model Context Protocol, Agentic AI, Node.js, REST API, gRPC, Vector Databases

Good to Have Skills: Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, vector databases like pgvector and Pinecone, enterprise software development, backend engineering, systems integration, cloud-native microservices, SAP web services integration, enterprise ticketing tools like JIRA/BMC Helix, multi-agent swarms, OWASP Top 10 for LLMs, data-masking and encryption approaches.

Roles & Responsibilities:

• Design, build, and deploy end-to-end Generative AI use cases from initial proof-of-concept to robust production environments.
• Focus on Level 1 support automation and Level 0 self-healing infrastructure implementation.
• Implement engineering strategies to minimize Mean Time to Resolution and maximize autonomous ticket deflection.
• Drive project-level operational efficiencies through innovative technical solutions and design patterns.
• Identify high-volume, repetitive IT tasks suitable for agentic automation and develop solutions.
• Develop and maintain API integrations using REST and gRPC for connecting conversational layers to backend systems.
• Work with enterprise systems including SAP via web services and ticketing tools like JIRA/BMC Helix.
• Ensure security compliance following OWASP Top 10 for LLMs and implement data-masking/encryption approaches.

Experience Required: 5+ years of experience in enterprise software development, backend engineering, or systems integration with emphasis on Python, Node.js, or cloud-native microservices. Deep practical experience building applications with Large Language Models and designing RAG pipelines required.

Education: B-Tech or Equivalent Engineering Degree

Key Skills

Education

Any Graduate