AI Solutions Engineer - Advancement & Donor Engagement

Babson College; Wellesley (MA); Hybrid; USD 128,000 - 143,000; Full time

Job summary

You will work onsite 5 days a week, using platforms like Salesforce, Azure, and related tools to deploy agents, monitor outcomes, and drive adoption across departments. A strong foundation in AI, data governance, and responsible AI practices is required.

Qualifications

• Bachelor’s Degree or related field and equivalent applied AI experience.
• 4+ years of experience developing, integrating, or deploying enterprise software, automation, analytics, data, or AI solutions, including hands-on experience building generative AI applications.
• Proficiency in SQL and Python programming.
• Experience with CRM data such as donor, prospect, campaign, or engagement data.
• Hands-on experience with AI backend services, AI agents or agentic workflows, API integrations, workflow automation, testing, debugging, and documentation.
• Strong problem-solving and product-thinking with rapid prototyping, testing, and productionizing solutions.

Responsibilities

• Design, develop, deploy, and improve enterprise AI solutions leveraging Advancement CRM data, Salesforce, enterprise AI platforms, APIs, and related technologies.
• Define and track business outcomes including productivity gains, fundraising impact, and ROI.
• Collaborate with Advancement staff, IT, Analytics, CRM admins, data governance, and end users to design, test, and deploy AI-enabled services and workflows.
• Design and deploy enterprise-wide AI agents and agentic workflows to retrieve information, recommend actions, and automate processes.

Skills

SQL

Python programming

CRM data

AI agent development

Education

Bachelor’s Degree in Computer Science, Data Science, Analytics, Information Systems, or related field

Tools

Azure

Azure AI Studio

Salesforce

Salesforce Education Cloud

Tableau

MuleSoft

Foundry

Advancement CRM

Job description

You will work onsite 5 days a week, using platforms like Salesforce, Azure, and related tools to deploy agents, monitor outcomes, and drive adoption across departments. A strong foundation in AI, data governance, and responsible AI practices is required.