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.

AI Lead Software Engineer

Social workers and non-profit organizations need better support - information, tools and coaching - to maximize their impact on communities. As an AI Lead Software Engineer, you will join an inclusive team that celebrates diverse backgrounds and expertise to address this critical need. 

You will help us build AI solutions that deliver services better and faster through workflow optimization, adaptive case management, and predictive analytics. Together, we will create agents that automate administrative burdens, reduce reporting time from hours to minutes, and enable data-driven insights—ultimately allowing social workers to focus their limited resources on what matters most: direct human connection with clients and communities.

What You'll Do

You will design and implement LLM-based agentic applications, run experiments, establish technical patterns for the team and mentor other engineers. You will write code 90%+ of the time and iterate with the frequency of a startup. This is what you can expect to do in this role:

• Design and implement AI agents using LLMs, vector databases, orchestration frameworks and connect to external systems using MCP.

• Define architectural patterns for prompt engineering, agent workflows, and system integration.

• Build on AWS (Bedrock, Lambda, DynamoDB).

• Establish and execute testing and evaluation strategies for non-deterministic AI systems.

• Partner with product teams to scope and plan, interview customers to gather feedback and boost adoption.

• Work directly with our Chief Architect and SVP of Engineering, they are both contributing code to our AI solutions.

Requirements

The technical experience that matters most to us includes:

• Building and shipping code to production in "startup mode" - releasing frequently, incorporating user feedback, continuous refactoring to preserve code quality while moving fast. 

• Using AI-assisted development tools like Cursor, Windsurf or Claude Code.

• Building and deploying LLM-based production systems, including MCP connectors and RAG solutions.

• Experience with AI frameworks (LangChain, LlamaIndex, etc.) or equivalent experience with complex software systems and eagerness to learn AI-specific tools.

• AWS knowledge, particularly managed AI services.

• Bonus points for:

  • Open source AI contributions.

  • Experience with AI evaluation and observability at scale.

  • Model training or fine-tuning

This job does NOT have a "years of experience" requirement and not all requirements are mandatory: while we do expect software engineering experience with AI/ML systems and AWS, we value passion and curiosity about AI's transformative potential over years of experience, and that is why we are warmly encouraging you to apply even if you don't meet every qualification listed. 

Why Diverse Backgrounds Matter for This Role

• Building AI tools for nonprofits isn't like building another SaaS dashboard. Social workers deal with complex, messy human problems that don't fit neat categories. If the entire engineering team comes from traditional tech companies, we're going to miss how these tools actually get used in the field.

• Someone who's worked in healthcare understands compliance headaches and data sensitivity in ways that matter for case management systems. An engineer who's navigated government bureaucracy knows why workflow automation needs to account for bizarre edge cases and manual overrides. If you've worked at a startup that failed, you understand resource constraints that nonprofits face daily.

• Different educational paths also matter - someone who studied social work before switching to engineering will spot usability pro