Data Engineer

JITO; Ambala; Remote; INR 1,200,000 - 2,400,000; Full time

Job summary

SROT AI, a senior India-based team, is hiring a full-stack data engineer to work with a US enterprise client in advanced manufacturing and industrial robotics. You'll join our three-person team, which builds and runs the platform the client's teams use every day for data, tools and AI.

You'll own work end to end: the data pipelines, the platform's features, the numbers the business runs on, and the AI tools on top.

Qualifications

• 2+ years building and running production software or data systems.
• Strong foundations in SQL, Python in production, TypeScript and React.
• Experience with AWS, Docker, Git and Linux.

Responsibilities

• Build features end to end: a page in Next.js and React, the FastAPI endpoint and SQL behind it, the migration, the tests and the release.
• Own data pipelines: Dagster jobs that pull from the warehouse (Redshift, dbt) and from systems such as NetSuite, Airtable, Jira and New Relic. Keep them correct, fast and observable.
• Make the numbers right: metrics like throughput, cycle time and mean time between failures go in front of leadership. Trace a wrong number to its source, fix it there, and write the definition down.
• Take requests from the people who use the platform: find the real question behind the ask, build the answer, and explain it in plain words.
• Build AI into the platform: the MCP connector, the assistant in the app and in Slack, and AI-assisted workflows where a person approves every change. Keep it model-agnostic: the data stays in the platform and models can be swapped.
• Run what you ship: releases, AWS infrastructure, access and incidents.
• Shape what comes next: propose new tools, design them, and say so when something shouldn't be built.

Skills

Next.js

Git

Docker

Python

AWS

React

SQL

TypeScript

Job description

Job Type: FullTimePermanent

Location: Ambala

Work Mode: Remote

Experience: MidLevel

Travel Requirements: Fully remote, India. Some meetings fall in the Indian evening (US morning).

Skills

• Next.js
• Git
• Docker
• Python
• AWS
• React
• SQL
• TypeScript

SROT AI, a senior India-based team, is hiring a full-stack data engineer to work with a US enterprise client in advanced manufacturing and industrial robotics. You'll join our three-person team, which builds and runs the platform the client's teams use every day for data, tools and AI. You'll own work end to end: the data pipelines, the platform's features, the numbers the business runs on, and the AI tools on top. Use of the platform has grown fast and the team is taking on new AI work, so we're adding a fourth builder. You'll work directly with Shrenik Jain, our founder, who leads product, architecture and technical direction, and our two staff engineers, Ansh Jain and Jigar Joshi. The platform brings the robot fleet, operations, supply chain and maintenance into one place where people look, ask and act, with an AI assistant in the app and in Slack and an MCP connector for Claude or ChatGPT. We release to production most working days: about 100 releases in the last ten weeks. We want an owner and a critical thinker. You use AI to move fast, and you still understand why the system is built the way it is. What we're looking for: ownership, critical thinking, depth (not just prompting), self-learning and forward thinking. Strong foundations in SQL and data modeling, Python in production, TypeScript and React, Git and code review, Linux and a cloud platform (AWS for us). Clear English, written and spoken. 2+ years building and running production software or data systems. We hire at mid-level or senior and set the level to the person. Our stack (you don't need all of it on day one): Next.js, React, TypeScript · Python, FastAPI, SQL · PostgreSQL on AWS RDS · Dagster · Redshift, dbt · MCP server, Claude API, AWS Bedrock · AWS, Docker, Terraform, GitHub Actions.

Responsibilities

• Build features end to end: a page in Next.js and React, the FastAPI endpoint and SQL behind it, the migration, the tests and the release.
• Own data pipelines: Dagster jobs that pull from the warehouse (Redshift, dbt) and from systems such as NetSuite, Airtable, Jira and New Relic. Keep them correct, fast and observable.
• Make the numbers right: metrics like throughput, cycle time and mean time between failures go in front of leadership. Trace a wrong number to its source, fix it there, and write the definition down.
• Take requests from the people who use the platform: find the real question behind the ask, build the answer, and explain it in plain words.
• Build AI into the platform: the MCP connector, the assistant in the app and in Slack, and AI-assisted workflows where a person approves every change. Keep it model-agnostic: the data stays in the platform and models can be swapped.
• Run what you ship: releases, AWS infrastructure, access and incidents.
• Shape what comes next: propose new tools, design them, and say so when something shouldn't be built.

Your first 90 days

• By day 30: you've shipped fixes and features to production, and you can trace data from a robot cell to a page in the platform.
• By day 60: you own a pipeline and a user-facing feature end to end, and you handle requests from ask to answer.
• By day 90: you own an area of the platform, review others' work, and have proposed one improvement backed by data.