Hiring: Senior Engineer - Data & AI (Generative AI)

Mtoag Technology Pvt Ltd; Jaipur; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Mtoag Technology Pvt Ltd in India seeks a Senior Engineer (Data/AI & Generative AI) to build end-to-end data pipelines, feature stores, and production-grade LLM apps. You’ll implement scalable architectures with strong engineering discipline and reliability.

You’ll work hybrid or on-site in India, collaborating with product and engineering teams to ship robust APIs and services, integrate ML/LLM tooling, and monitor performance with CI/CD and observability practices.

Qualifications

• Backend engineering fundamentals and system design.
• Proficiency in Python/Node, APIs, databases, and cloud basics.
• Exposure to ML/LLM tooling (prompting, embeddings, vector DBs, evaluation).

Responsibilities

• Design, build, and operate data pipelines and feature stores.
• Develop LLM/RAG workflows with evaluation and monitoring.
• Ship production APIs and services with reliability and security best practices.
• Collaborate with product and engineering teams to turn ideas into deliverables.

Skills

Backend engineering

System design

Python

Node.js

APIs

Databases

Cloud basics

CI/CD

Observability

ML/LLM tooling

Tools

ML/LLM tooling

Prompting

Embeddings

Vector DBs

Evaluation

Job description

Senior Engineer (Data/AI & Generative AI)

Build data and AI systems end-to-end — from pipelines and evaluation to production-grade LLM apps. If you enjoy shipping reliable AI features with strong engineering rigor, we’d love to hear from you.

Hybrid / On Site India Full Time

Responsibilities

• Design, build, and operate data pipelines and feature stores.
• Develop LLM/RAG workflows with evaluation and monitoring.
• Ship production APIs and services with reliability and security best practices.
• Collaborate with product and engineering teams to turn ideas into deliverables.

Requirements

• Strong fundamentals in backend engineering and system design.
• Hands‑on experience with Python/Node, APIs, databases, and cloud basics.
• Practical exposure to ML/LLM tooling (prompting, embeddings, vector DBs, evaluation).
• Comfortable with testing, CI/CD, and observability.