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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
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
process and analyze large datasets using snowflake
design, build, and maintain etl pipelines
develop data models supporting analytics and ai workloads
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
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
special accommodation
if you are a person with a disability and need assistance applying for a job, please submit a request.
Lean on us to help you make life better
we think and act like owners.
We are committed to making our customers successful.
We are bold in our aspirations while moving forward with humility and integrity.
We foster inspired teams.
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