Software Development Advisor

NTT DATA, Inc.; Dadri; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

NTT DATA, Inc. is seeking an experienced Engineer to build enterprise-grade AI agents that handle thousands of customer conversations daily.

You will work closely with the CX team to design, implement, and validate agent capabilities using React, TypeScript, and Go. The role requires 4+ years of hands-on software development, strong customer-facing collaboration, and a CS-related degree or equivalent experience.

Qualifications

• 4+ years hands-on software development of highly technical products.
• Past experience at or above the level of Senior Software Engineer.
• Experience crafting and tailoring messages for potential customers, including executives.
• Degree in Computer Science or related field, or equivalent experience.

Responsibilities

• Build the agent from scratch using product requirements.
• Develop, test scenarios including knowledge retrieval and support journeys, and write simulation tests.
• Interfacing with the client in a product capacity to connect to APIs/databases.
• Review live conversations and client feedback using the experience manager.
• Identify negative conversations, create issues, and track resolutions.
• Regularly check in, improve, and evaluate agent performance.

Skills

AI agent dev

Client facing

Senior software eng

LLM basics

Education

Bachelor's degree in Computer Science or related field

Tools

React

Typescript

Go

Python

Git

Job description

Job Description

What youll do

• Build enterprise-grade AI agents: As an Agent Engineer, you will be responsible for partnering directly with our CX team to build and ship AI agents that handle thousands of customer conversations a day.

What you’ll bring

• 4+ years experience in hands-on software development of highly technical products.
• Past experience in Software Development or other similar hands-on development roles at or above the level of Senior Software Engineer.
• Experience crafting and tailoring a message for potential customers, including executives.
• Degree in Computer Science or related field, or equivalent professional experience.

Skill Requirements

• AI-related experience (experience developing code based AI agents such as conversational AI agents a plus).
• Experience with React, Typescript, and Go.
• Experience in Python
• Past roles that interface with end customers to influence software development.
• Engineers working on building AI agents should be self-sufficient engineers at a senior level. They should be completely comfortable with normal software development lifecycles and be able to write code independently, including building components, integrating with APIs, and testing/deployment
• The AI agent is built programmatically using code. It is explicitly NOT a no-code/low-code application. Everything including setup, permissions, version control, development, testing, and deployment are done via extensive coding workflows.
• Engineers should be highly experienced in ReactJS and Typescript, comfortable with VCS using Git, and other standard engineering workflows. Should have a working understanding of LLMs and writing API integrations in Typescript.
• Engineers should have a comprehensive understanding of React JS, especially core concepts/philosophies of developing with React and front-end frameworks in general. The Agent SDK has some important distinctions from React, but understanding of React development lifecycle and component lifecycle will enable engineers to grasp these differences and develop against them.

Most engineers will primarily need to know

• React (Intermedia to Advanced)
• Python
• Typescript (Intermedia to Advanced )
• LLM/prompt engineering basics
• Github/version control
• Terminal

Typical AI Engineer Role and Responsibility

• build the agent from scratch using product requirements
• This includes developing the agent, testing different scenarios including knowledge retrieval and support journeys, and writing simulation tests
• This can (should) also include interfacing directly with the client in a product capacity, ensuring that the agent is meeting its needs and can connect to all necessary APIs/databases to do its job
• Review live conversations and client feedback, using the experience manager
• This includes identifying negative conversations using evaluation tools, creating issues for bad conversations, receiving issues from the client, and so on
• This is the steady state of the agent -- regularly checking in, making improvements, evaluating metrics