AI Engineer

Regal Rexnord; Hyderabad; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Regal Rexnord is seeking a software engineer to build GenAI-enabled features and internal AI assistants in a hybrid on-site role with remote flexibility at a Regal Rexnord location. You will work with LLMs, RAG pipelines, embeddings, and AI platforms (Azure AI Foundry, Azure OpenAI, OpenAI APIs, AWS Bedrock), contribute to SDLC, CI/CD, and secure engineering practices.

Bachelor’s degree in CS/IT/AI and 0–2 years of experience; hands-on with Python, REST APIs, and AI-assisted development tools

Qualifications

• Bachelor’s degree in a technical field.
• 0–2 years of software development experience in full-stack, backend, or GenAI projects.
• Proficiency with Python, REST APIs, and web app development.
• Practical understanding of LLMs, prompt engineering, RAG, embeddings.
• Familiarity with agile SDLC, code reviews, testing, and documentation.

Responsibilities

• Build GenAI-enabled features using LLMs, prompt engineering, RAG pipelines, embeddings, and vector search.
• Develop internal AI assistants, chatbots, and workflow automation tools to improve engineering and business workflows.
• Implement backend services, API integrations, authentication, logging, and validations.
• Build and enhance RAG pipelines from enterprise data sources.
• Collaborate with product owners and engineers to translate business needs into software.
• Participate in code reviews, testing, CI/CD, and release readiness.

Skills

GenAI development

Python

REST APIs

LLMs

Prompt engineering

Docker

CI/CD

GitHub Copilot

Cursor AI

Education

Bachelor’s degree in Computer Science or related field

Tools

Azure AI Foundry

Azure OpenAI

OpenAI APIs

AWS Bedrock

Cursor AI

GitHub Copilot

GitHub SpecKit

Job description

Work Model: You’ll work in a hybrid model, onsite at your designated Regal Rexnord location, with flexibility to work remotely.

____________________

Roles and Responsibilities:

• Build GenAI-enabled application features using large language models (LLMs), prompt engineering, RAG pipelines, embeddings, vector search, and agentic AI patterns.
• Develop internal AI assistants, chatbots, workflow automation tools, intelligent dashboards, and productivity applications to improve engineering and business workflows.
• Implement backend services, API integrations, data processing logic, authentication support, error handling, logging, and application-level validations.
• Build and enhance RAG pipelines using internal documents, product documentation, user guides, technical specifications, requirements, and structured or unstructured enterprise data sources.
• Work with AI platforms and LLM APIs such as Azure AI Foundry, Azure OpenAI, OpenAI-compatible APIs, AWS Bedrock, or similar enterprise AI platforms.
• Use AI-assisted development tools such as Cursor AI, GitHub Copilot, Claude Code, and GitHub SpecKit to improve productivity, code quality, and SDLC discipline.
• Apply specification-driven development practices by contributing to specifications, implementation plans, task breakdowns, acceptance criteria, and technical documentation.
• Collaborate with product owners, business analysts, architects, engineering managers, and senior engineers to convert business needs into working software features.
• Participate in code reviews, debugging, unit testing, integration testing, defect fixing, CI/CD activities, and release readiness reviews.
• Support Docker-based deployment, environment configuration, cloud deployment basics, and operational troubleshooting for developed applications.
• Follow secure engineering and responsible AI practices, including data privacy, access control, prompt safety, output validation, and safe handling of enterprise information.
• Continuously learn and evaluate emerging GenAI frameworks, AI coding tools, agentic AI patterns, and modern software engineering practices.

Qualifications:

• Education: Bachelor’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or a related technical field.
• Experience: 0–2 years of professional software development experience, internship experience, or equivalent hands‑on project experience in full‑stack, backend, or GenAI application development.
• Technical Exposure: Hands‑on experience with Python, REST APIs, web application development, Git/GitHub, and AI‑assisted development tools such as Cursor AI, GitHub Copilot, or similar tools.
• GenAI Exposure: Practical understanding of LLMs, prompt engineering, RAG, embeddings, AI APIs, or agentic workflow concepts.
• Development Practices: Familiarity with agile development, SDLC, code reviews, testing, documentation, and incremental delivery of software features.

Skills:

• Hands‑on understanding of backend development using FastAPI, Flask, Django, or similar Python frameworks.
• Ability to build REST APIs, integrate external APIs, process JSON data, and troubleshoot application issues.
• Basic understanding of databases such as PostgreSQL, SQL Server, SQLite, DuckDB, MongoDB, or vector databases such as pgvector, FAISS, Chroma, Pinecone, or Azure AI Search.
• Exposure to GenAI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, Haystack, Agno, or similar frameworks is preferred.
• Understanding of Docker, CI/CD basics, cloud deployment basics, and application configuration management is preferred.
• Ability to understand requirements, break down work into tasks, and deliver working software in collaboration with the team.
• Good communication, documentation, analytical thinking, ownership mindset, and willingness to learn new technologies.
• Awareness of responsible AI practices such as hallucination control, prompt injection risk, output validation, privacy, security, and access control is a plus.

Preferred / Good to Have:

• Experience building GenAI applications such as chat assistants, document Q&A systems, summarization tools, workflow assistants, or intelligent automation tools.
• Exposure to GitHub SpecKit commands and artifacts such as /speckit.constitution, /speckit.specify, /speckit.plan, and /speckit.tasks.
• Experience with Azure AI Foundry, Azure OpenAI, OpenAI APIs, AWS Bedrock, or OpenAI-compatible model endpoints.
• Understanding of LLMOps or MLOps concepts such as prompt versioning, evaluation, observability, latency, token cost, monitoring, and feedback loops.
• Ability to explain technical work clearly through documentation, demos, diagrams, and status updates.

About Regal Rexnord

Regal Rexnord is a publicly held global industrial manufacturer with 30,000 associates around the world who help create a better tomorrow by providing sustainable solutions that power, transmit and control motion. The Company’s electric motors and air moving subsystems provide the power to create motion. A portfolio of highly engineered power transmission components and subsystems efficiently transmits motion to power industrial applications. The Company’s automation offering, comprised of controls, actuators, drives, and precision motors, controls motion in applications ranging from factory automation to precision control in surgical tools.

The Company’s end markets benefit from meaningful secular demand tailwinds, and include factory automation, food & beverage, aerospace, medical, data center, warehouse, alternative energy, residential and commercial buildings, general industrial, construction, metals and mining, and agriculture.

Regal Rexnord is comprised of three operating segments: Industrial Powertrain Solutions, Power Efficiency Solutions, and Automation & Motion Control. Regal Rexnord has offices and manufacturing, sales and service facilities worldwide. For more information, including a copy of our Sustainability Report, visit RegalRexnord.com.

Regal Rexnord is a global leader in sustainable motion control and power transmission solutions, enhancing efficiency across commercial, industrial, and residential applications.

Electric Power Transmission, Control, and Distribution Utilities

Company size 10,001+ employees

Company type Public company Founded 1955

Momentum

Team growth

Momentum

Team growth

7% in 12 mo

5,808 employees on LinkedIn

Sep 22 May 26

Footprint

Where they work

111 W Michigan St, Milwaukee, Wisconsin 53203, US