AI Agentic Developer

NTT DATA North America; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

NTT DATA North America is looking for an experienced software/integration engineer to drive enterprise integrations. The role emphasizes hands-on MuleSoft work, API-led design, and AI/Agentic AI initiatives, with collaboration across global stakeholders in multiple time zones.

The candidate should have 4–5 years in software/integration, including ~2 years in AI, and can deliver production integrations using REST/SOAP, JSON/XML, and data workflows.

Qualifications

• 4–5 years of software/integration engineering experience, incl. ~2 years AI experience.
• Proven delivery of production integrations in an enterprise environment.
• Hands-on MuleSoft Anypoint Platform experience; certification preferred.
• Strong REST/SOAP, JSON/XML, OAuth, and API-security fundamentals.
• Exposure to SAP order entry, pricing, drop-ship, and customer master data.
• Experience with AI concepts: LLM agents, prompt engineering, agentic workflows.
• Knowledge of LangChain / LangGraph; RAG pipelines; vector stores.
• Python scripting for automation; CI/CD, testing, and documentation.

Responsibilities

• Deliver enterprise integrations with MuleSoft, API-led design, and CloudHub deployment.
• Translate business rules into deterministic automation logic for scalable solutions.
• Collaborate with global stakeholders across overlapping time zones.
• Contribute to building/maintaining AI agent workflows and data pipelines.
• Support UAT, go-live, and maintain clear technical docs.

Skills

AI / Agentic AI experience

CI/CD

Python scripting

communication across time zones

Tools

MuleSoft Anypoint Platform

REST/SOAP APIs

JSON/XML, OAuth

SAP order entry / pricing / master data

LangChain / LangGraph

Databricks / MLflow

vector databases

Job description

• 4–5 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.

General & Experience

• 4–5 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.