AI Developer

JD#1 Enterprise AI Developer Mandatory Skills Artificial Intelligence,Python,Chatbot,AWS,Model Context Protocol (MCP),Agentic Ai Job Description Core Engineering Background 5+ years of experience in enterprise software development, backend engineering, or systems integration, with a heavy emphasis on Python, node.js, or cloud-native microservices. Generative AI Core Competency Deep, practical experience building applications with Large Language Models (LLMs), designing Retrieval-Augmented Generation (RAG) pipelines, and working with vector databases (e.g., pgvector, Pinecone, or custom S3-backed vector files). Integration Expertise Demonstrated mastery in API development (REST, gRPC) and connecting conversational layers to complex backend transaction systems (specifically SAP via web services and enterprise ticketing tools like JIRA/BMC Helix). Protocol & Systems Familiarity Exposure to modern AI agent communication frameworks, multi-agent swarms, or open standards like the Model Context Protocol (MCP) . Security Awareness Solid understanding of the OWASP Top 10 for LLMs and standard data-masking/encryption approaches. Education Qualificaiton B-Tech or Equivalent Engineering Degree Roles & Responsibilities 1. Hands-On Development & Core Architecture (Catalyst Domain) Production-Grade AI Engineering Design, build, and deploy end-to-end Generative AI use cases from initial proof-of-concept (POC) to robust production environments, focusing on Level 1 (L1) support automation and Level 0 (L0) self-healing infrastructure. Performance Optimization Implement engineering strategies directly targeted at minimizing Mean Time to Resolution (MTTR), maximizing autonomous ticket deflection, and driving project-level operational efficiencies. Proactive Prototyping Bring innovative technical solutions and technical design patterns to the table, identifying high-volume, repetitive IT tasks ripe for agentic automation.