Senior Software Engineer

Bonterra exists to propel every doer of good to their peak impact. We measure that impact against our vision to increase the giving rate as a percentage of GDP from 2% to 3% by 2033. We know that this goal is lofty, but we are confident that the right technology and expertise will strengthen trust in the sector, allowing the social good industry to accelerate growth and reach peak impact. Bonterra's differentiated, end-to-end solutions collectively support a unique network of over 20,000 customers, including over 16,000 nonprofit organizations and over 50 percent of Fortune 100 companies. Learn more at bonterratech.com.

Who You Are:

Are you an innovative senior software engineer who has successfully utilized AI and AWS to build large-scale product offerings? Can you help teams understand how AI can accelerate the delivery of products with speed and quality? Are you passionate about leveraging the latest technologies to create meaningful change, particularly in the not-for-profit sector, where your work can empower organizations nationwide to increase their impact in communities?

At Bonterra, we are seeking a highly experienced senior software engineer who is passionate about designing and implementing AI and cloud-first solutions hosted on Amazon Web Services (AWS). Their expertise will help us meet the unique needs of our diverse range of nonprofit clients, ensuring they have access to feature-rich solutions that enhance their effectiveness in measuring the impact of their activities in communities. The ideal candidate will have extensive experience with cloud architecture, software development, and AI, enabling us to deliver scalable and impactful solutions for our clients. They will work with the lead software engineer and the software engineering team to design, develop, and deliver applications that integrate and visualize data across Bonterra's suite of products.

What you will do:  

• Contribute to a High-Performing Team: Collaborate with a talented group of engineers to deliver innovative solutions while participating in a culture of continuous learning and exploration of the latest technologies.

• Provide mentorship: Mentor and guide team members by sharing expertise, fostering collaboration, and providing constructive feedback to develop their skills.

• Collaborate with the Lead Engineer, Engineering Managers, and Architects: Work closely with the lead software engineer and architects to assist in the design, development, and delivery of large-scale data applications that utilize LLMs and other AI tools, enhancing product delivery.

• Be an AI and Cloud Advocate: Stay informed about emerging AI technologies and identify opportunities to leverage them for improving solution delivery while maintaining high-quality standards.

• Work with QA Engineers: Partner with QA engineers to help create and maintain automated test suites, ensuring robust product quality.

• Engage with Cross-Functional Teams: Collaborate with product managers, data engineers, and UX designers to help translate complex technical concepts into user-friendly solutions.

• Support Feature Development and Maintenance: Assist in the development of new features and platforms while also contributing to the maintenance of existing data and reporting applications.

• Collaborate with DevOps and SaaS Teams: Work alongside DevOps and SaaS teams to support the implementation and maintenance of CI/CD pipelines.

• Foster a Positive Company Culture: Contribute to a company culture that values cross-team collaboration and trust.

Requirements: 

• 5+ years of Software Development experience including design patterns, data structures, and test-driven development 

• Strong AI Foundation: Proven experience in applying machine learning and AI techniques to real-world data problems.

• Expertise with AWS cloud infrastructure and deployment models, including automation, orchestration, and scale.

• Experience building large-scale, durable, reliable, and scalable data applications in a cloud environment.

• Data Engineering Expertise: Deep understanding of data engineering principles, including data modeling, ETL processes, and data warehousing.

• Deep understanding of relational data modeling & practical experience with RDBMS and ETL tools such as AWS Glue, DBT, and SSIS.

• Track record of creating robust data pipelines using AWS services such as Amazon Redshift, Kinesis, DMS, and or alternate solutions using Snowflake

• In-depth experience with Enterprise Business Intelligence tools such as QuickSight, Looker, Tableau, and PowerBI.

• Agile Methodology: Experience working in Agile environments, such as Scrum or Kanban.