About this role
Overview
Esri’s Professional Services division is seeking a Software Development Engineer to support the evolution of geospatial data quality capabilities across the ArcGIS platform. In this role, you will design and develop the software used by a large community of GIS professionals to power the operations of their organizations.
In this position, you will design and develop software used by organizations across diverse markets and industries to ensure quality and consistency in their geospatial data holdings. You will be part of a talented cross-functional team of dynamic and passionate engineers who deliver Generative AI (GenAI) capabilities in data quality that enable our customers to make a difference in communities around the world.
As part of the Professional Services division, you will work closely with product teams, domain experts, and technical specialists to create robust, production-ready software that transforms and advances geospatial data quality. If you are passionate about geospatial technologies, AI-driven data quality management, and building scalable, high-performance distributed solutions, this role offers the opportunity to work on cutting-edge technologies that shape how organizations build, validate, and maintain accurate geospatial assets.
Responsibilities
- Develop Python-based machine learning and GenAI components that support geospatial data quality workflows
- Assist in building AI-driven features that help users assess, validate, and improve spatial data quality
- Contribute to GenAI-enabled pipelines using embeddings, vector search, and retrieval-augmented generation (RAG)
- Write well-tested, maintainable, and documented code that meets product quality standards
- Build software adhering to industry-standard design patterns, development methodologies, and deployment models, with a focus on AI-driven solutions
- Collaborate with cross-functional teams, including data scientists, developers, engineers, and product managers, to drive AI initiatives throughout the development lifecycle
- Work within Agile Scrum team environment, contributing to sprint planning, reviews, and continuous improvement efforts
Requirements
- 2+ years of professional software development or data science experience in similar roles with a focus on structured data analysis and Gen AI workflows
- Strong proficiency in Python, with experience implementing algorithms that operate on structured datasets
- Experience working with data transformation, aggregation, or feature construction as part of analytical or AI-driven workflows
- Understanding of object-oriented programming principles and backend software design
- Familiarity with machine learning concepts such as pattern recognition, similarity analysis, or predictive modeling
- Bachelor’s degree in computer science, mathematics, or a related STEM field
Recommended Qualifications
- Familiarity with similarity/semantic search, embedding-based approaches, or vector-based representations of data
- Experience analyzing large geospatial or structured datasets to uncover trends, inconsistencies, or quality issues
- Experience with Agile development practices and collaborative software teams
- Exposure to GenAI concepts such as prompt design, structured outputs, or contextual grounding
- Knowledge of the ArcGIS platform (ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise) is a plus
- Master’s degree in computer science, mathematics, or a related STEM field is a plus
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Total Rewards
Esri’s competitive total rewards strategy includes industry-leading health and welfare benefits: medical, dental, vision, basic and supplemental life insurance for employees (and their families), 401(k) and profit-sharing programs, minimum accrual of 80 hours of vacation leave, twelve paid holidays throughout the calendar year, and opportunities for personal and professional growth. Base salary is one component of our total rewards strategy. Compensation decisions and the base range for this role take into account many factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
The Company
At Esri, diversity is more than just a word on a map. When employees of different experiences, perspectives, backgrounds, and cultures come together, we are more innovative and ultimately a better place to work. We believe in having a diverse workforce that is unified under our mission of creating positive global change. We understand that diversity, equity, and inclusion is not a destination but an ongoing process. We are committed to the continuation of learning, growing, and changing our workplace so every employee can contribute to their life’s best work. Our commitment to these principles extends to the global communities we serve by creating positive change with GIS technology. For more information on Esri’s Racial Equity and Social Justice initiatives, please visit our website here.
If you don’t meet all of the preferred qualifications for this position, we encourage you to still apply!
Esri is an equal opportunity employer (EOE) and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need reasonable accommodation for any part of the employment process, please email [email protected] and let us know the nature of your request and your contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this e-mail address.
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Other facts
About Esri
Esri is the global market leader in geographic information system (GIS) software, location intelligence, and mapping. Since 1969, we have supported customers with geographic science and geospatial analytics, what we call The Science of Where. We take a geographic approach to problem-solving, brought to life by modern GIS technology.
What you'll do
- Develop Python-based machine learning and GenAI components to support geospatial data quality workflows. Collaborate with cross-functional teams to create robust, production-ready software that enhances data quality management.
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