AI Agentic Developer

NTT DATA BUSINESS SOLUTIONS; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS is seeking a seasoned professional with deep MuleSoft and AI experience to design, develop, and deploy enterprise integrations. You will work on API-led integration, DataWeave mappings, and CloudHub deployments while applying best practices in security, testing, and monitoring.

Additionally, you will explore agentic AI workflows, multi‑agent orchestration, and RAG pipelines, leveraging LangChain or LangGraph frameworks, and collaborate with global stakeholders across

Qualifications

• Hands‑on experience on the MuleSoft Anypoint Platform API‑led design, DataWeave, connectors, error handling, and CloudHub deployment.
• Strong REST/SOAP, JSON/XML, OAuth, and API‑security fundamentals.
• Exposure to SAP order entry, pricing, drop‑ship, and customer master data; translate business rules into automation logic.
• Exposure to AI/ML concepts, LLM‑based agents, prompt engineering, or agentic workflows.
• Understanding of agent architectures multi‑agent orchestration, tool‑use patterns, and autonomous task execution.
• Knowledge of agentic frameworks such as LangChain, LangGraph, or similar.
• Experience building or integrating RAG pipelines with vector databases.
• Familiarity with caching strategies and memory/context management for AI agents.
• Experience with agent deployment and serving (Databricks preferred), MLflow, or similar platforms.
• Familiarity with MCP or AI‑assisted automation.
• Python scripting for automation or tooling.
• CI/CD, version control, automated testing, and monitoring; writes clear technical documentation.
• Self‑directed delivery with strong communication across overlapping time zones.

Skills

MuleSoft integration

AI agent concepts

LangChain / LangGraph

RAG pipelines

Python scripting

CI/CD

Documentation

Stakeholder communication

Multi‑cloud / Databricks

API security basics

Tools

MuleSoft Anypoint Platform

DataWeave

CloudHub

Databricks

MLflow

Job description

General Experience

• 45 years of overall software / integration engineering experience, including approximately 2 years of hands‑on AI / Agentic AI experience.
• Proven delivery of production integrations in an enterprise environment.

MuleSoft Integration Expertise

• Hands‑on experience on the MuleSoft Anypoint Platform API‑led design, DataWeave, connectors, error handling, and CloudHub deployment. MuleSoft Developer certification preferred.
• Strong REST/SOAP, JSON/XML, OAuth, and API‑security fundamentals; comfortable with email, file, and database connectivity patterns.
• Exposure to SAP order entry, pricing, drop‑ship, and customer master data is a strong plus; ability to translate business rules into deterministic automation logic.

AI / Agentic AI Skill Set

• Exposure to AI/ML concepts LLM‑based agents, prompt engineering, or agentic workflows.
• Understanding of AI agent architectures multi‑agent orchestration, tool‑use patterns, and autonomous task execution.
• Knowledge of agentic frameworks such as LangChain, LangGraph, or similar.
• Experience building or integrating RAG (Retrieval‑Augmented Generation) pipelines with vector databases.
• Familiarity with caching strategies and memory / context management for AI agents (conversation history, session persistence, vector stores).
• Experience with agent deployment and serving (Databricks preferred), MLflow, or similar platforms.
• Familiarity with MCP (Model Context Protocol) or AI‑assisted automation.
• Python scripting for automation or tooling.

Engineering Practices Ways of Working

• CI/CD, version control, automated testing, and monitoring; writes clear technical documentation and supports UAT and go‑live.
• Self‑directed delivery with strong communication skills; comfortable operating across overlapping time zones with global stakeholders.

Nice to Have

• MuleSoft Certified Developer / Integration Architect certification.
• Experience with EDI, cXML, Coupa and B2B onboarding integrations.
• Exposure to document‑extraction and evaluation of agent accuracy.