AI Engineer

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

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Scope of Role:

We are seeking an AI Engineer to join our Data & AI engineering team. The ideal candidate has hands-on

experience building GenAI applications, full-stack Python applications, internal productivity tools, and AIenabled workflow applications using modern engineering practices and AI-assisted development tools such as

Cursor AI, GitHub Copilot, and GitHub SpecKit.

Candidate will be responsible for designing, developing, testing, and supporting AI-enabled software

applications, including chat assistants, RAG-based knowledge applications, agentic workflows, intelligent

dashboards, APIs, and internal automation tools.

This position encompasses the full software development lifecycle, including requirements understanding,

specification-driven development, solution design, coding, testing, documentation, deployment support, and

continuous improvement.

KEY RESPONSIBILITIES

• Design, develop, and maintain full-stack applications using Python, FastAPI, React, JavaScript/TypeScript, REST

APIs, and modern web development practices.

• 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.

Requirements:

• 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:

• Strong programming skills in Python and basic understanding of JavaScript/TypeScript, React, HTML, and CSS.

• 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, …