Sr. Software Engineer – Generative AI & Assistants, ArcGIS Pro

As a Sr. Software Engineer – Generative AI & Assistants at Esri, you will be involved in designing and implementing an AI Copilot for ArcGIS Pro. Your responsibilities include developing AI models and algorithms primarily in C# or Python that focus on natural language generation and understanding. You'll also write scalable and maintainable code, collaborate with cross-functional teams to gather user requirements, and translate these into high-performance software solutions, all while keeping up with the latest AI advancements.

Esri requires candidates for the Sr. Software Engineer – Generative AI & Assistants position to have a Bachelor’s degree in fields like computer science, GIS, or Mathematics. You should have a minimum of 5 years of experience in robust code development, especially using C# on the .NET platform. Familiarity with AI concepts, experience with large language models, and knowledge of machine learning frameworks like TensorFlow or PyTorch are highly recommended.

For the Sr. Software Engineer – Generative AI & Assistants role at Esri, proficiency in C# and Python is essential, as these will be your primary languages for developing AI models and algorithms. Knowledge of C++ is also beneficial, in addition to familiarity with REST APIs and web services. A good grasp of programming best practices will help ensure code quality and maintainability.

At Esri, the culture is collaborative and innovation-driven. As a Sr. Software Engineer – Generative AI & Assistants, you'll work with a diverse global team, consisting of software engineers, product managers, and designers, all committed to delivering the best GIS solutions. Esri promotes an inclusive environment where diverse perspectives are valued, allowing you to contribute your ideas and grow within the organization.

In the Sr. Software Engineer – Generative AI & Assistants role at Esri, there are numerous opportunities for professional growth. Esri encourages continuous learning and offers access to training programs, workshops, and conferences. Additionally, with a variety of projects and technologies to engage with, you can enhance your skills in AI and machine learning, propelling your career within the organization and the tech industry.

When designing AI models for ArcGIS Pro, start by understanding user needs and the specific problem the models aim to solve. Research the latest advancements in AI and machine learning, particularly in natural language processing. Collaborate with your team to identify the most suitable algorithms and frameworks, such as those that leverage large language models. Prototyping early and iterating based on feedback ensures that your design aligns with user expectations.

Discuss your experience with popular machine learning frameworks like TensorFlow or PyTorch. Highlight specific projects where you have implemented machine learning algorithms, emphasizing your role in the development process and the results achieved. Demonstrating your hands-on experience and familiarity with these tools will show your preparedness for the Sr. Software Engineer position at Esri.

Natural language processing (NLP) is essential for AI Copilot functionalities as it enables users to interact with GIS systems using everyday language. Emphasize your understanding of how NLP can enhance user experience by providing intuitive responses, simplifying complex queries, and making geographic data more accessible. You can draw on examples of how effective NLP implementations have led to improved user satisfaction in previous projects.

To write maintainable code, I follow established coding standards and design patterns, ensuring code clarity and consistency. I also emphasize the importance of documentation, commenting on complex sections to facilitate understanding for future developers. Using version control tools like GIT for code management helps track changes and encourages collaborative development. Regular code reviews contribute to improved code quality and facilitate knowledge sharing among team members.

Staying updated on AI and machine learning advancements involves regular engagement with industry publications, online courses, webinars, and participation in tech forums. I also value networking with professionals in the field and attending relevant conferences whenever possible. This knowledge not only keeps my skills fresh but also allows me to bring innovative ideas to my team at Esri.

Collaboration with cross-functional teams is key in software development. I ensure effective communication by actively listening to team members from different disciplines such as engineering, design, and product management. I facilitate discussions to gather diverse perspectives and foster a cohesive environment, balancing technical requirements with user needs. Sharing updates and receiving feedback regularly strengthens collaboration and helps achieve project goals.

In a professional setting, I am most comfortable with C# and Python, having used them extensively in my previous roles. I have developed many projects emphasizing performance, scalability, and maintainability. I also bring experience in C++ which, although less frequent, has provided me with a broad understanding of programming paradigms and methodologies that are beneficial in problem-solving within software development.

Developing AI models can present several challenges, such as dealing with data quality issues or ensuring model performance under diverse user scenarios. When faced with these challenges, I employ comprehensive data validation and preprocessing techniques, along with iterative fine-tuning of models. Collaboration with domain experts for insights also plays a crucial role in overcoming obstacles, allowing for refinement and ensuring relevance in output.

To ensure data security and privacy in AI applications, I prioritize implementing industry-standard security protocols and encryption methods when handling sensitive data. This involves setting strict access controls and conducting periodic audits. Additionally, I am aware of comprehensive privacy frameworks such as GDPR, and I design systems that allow users to manage their data preferences effectively.

I want to work at Esri because I am passionate about creating innovative solutions that drive positive change through technology. The company’s commitment to diversity and inclusion aligns with my values and I admire Esri’s focus on meaningful applications of GIS technology. The opportunity to collaborate with a talented team while leading advancements in AI that improve accessibility to spatial data is particularly appealing to me.