Ingersoll Rand is committed to achieving workforce diversity reflective of our communities. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
Role Summary

Design and deliver Generative AI and data products that power AI assistants for sales and technical support teams across Ingersoll Rand. This role focuses on applied AI engineering and LLM‑based systems built on Snowflake, Cortex AI, Vertex AI, and cloud‑native platforms .

You will partner with engineering and business teams to transform AI prototypes into reliable, production‑ready solutions , owning delivery with a strong technical foundation and product mindset .
The Core Challenge

Ingersoll Rand is expanding the use of Generative AI to enhance sales and technical support workflows. While LLMs enable rapid experimentation, delivering trusted, governed AI solutions at enterprise scale requires disciplined engineering .

This role bridges experimentation and production by building AI systems that integrate seamlessly with enterprise data, analytics, and operational platforms .
Key Responsibilities

Generative AI & AI Assistant Development
Design and deploy LLM‑powered AI assistants for sales and technical support use cases

Implement retrieval‑augmented generation (RAG) using embeddings, vector search, and enterprise data

Develop Generative AI solutions using Snowflake Cortex AI, Vertex AI, and external LLM APIs
Software Development
Design and develop web‑based AI applications ,



building backend services and features in Python that integrate AI models and enterprise data

Own the full software development lifecycle , writing clean, testable code with appropriate unit and integration tests

Build, test, and deploy AI solutions using modern pipelines, ensuring production reliability and scalability
Data Engineering & Analytics
Process and analyze large datasets using Snowflake

Design, build, and maintain ETL pipelines

Develop data models supporting analytics and AI workloads
Engineering & Platform Practices
Build reusable AI components, APIs, and shared services

Partner with platform and IT teams to ensure secure, standardized deployments

Contribute to engineering standards for testing, CI/CD, observability, and documentation
Visualization & Business Enablement
Develop dashboards and insights using Qlik

Communicate AI outcomes and insights to business stakeholders
Collaboration & Governance
Drive projects end‑to‑end with a product owner mindset

Ensure data security, compliance, and AI governance

Stay current with advances in AI and Generative AI technologies
Required Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, or a related field

5+ years of experience in AI engineering, data science, or machine learning

Strong proficiency in Python and SQL

Hands‑on experience with LLMs and Generative AI systems

Experience with Snowflake and cloud platforms

Strong communication and problem‑solving skills
Preferred Qualifications
Experience with Snowflake Cortex AI and Google Vertex AI

Experience with embeddings, vector databases, and RAG architectures

Manufacturing or industrial domain experience

Familiarity with MLOps practices
What This Role Is
An applied AI engineering role focused on production systems

A bridge between advanced AI capabilities and real business value

A role for engineers who thrive on ownership and impact

📌 Senior AI Engineer (Tlalnepantla de Baz)
🏢 Ingersoll Rand
📍 Tlalnepantla de Baz