Software Engineer
Ensures the accuracy and reliability of AI solutions deployed for government clients by conducting data validation, model performance testing, and quality audits using Python, statistical methods, SQL queries, and cloud services such as AWS.
The Company
Serving the People Who Serve the People
Granicus is driven by the excitement of building, implementing, and maintaining technology that is transforming the Govtech industry by bringing governments and its constituents together. We are on a mission to support our customers with meeting the needs of their communities and implementing our technology in ways that are equitable and inclusive. Granicus has consistently appeared on the GovTech 100 list over the past 5 years and has been recognized as the best companies to work on BuiltIn.
Over the last 25 years, we have served 5,500 federal, state, and local government agencies and more than 300 million citizen subscribers power an unmatched Subscriber Network that use our digital solutions to make the world a better place. With comprehensive cloud-based solutions for communications, government website design, meeting and agenda management software, records management, and digital services, Granicus empowers stronger relationships between government and residents across the U.S., U.K., Australia, New Zealand, and Canada. By simplifying interactions with residents, while disseminating critical information, Granicus brings governments closer to the people they serve—driving meaningful change for communities around the globe.
Want to know more? See more of what we do here.
Job Summary
The AI Quality & Evaluation Analyst is responsible for assessing the quality, correctness, completeness, and safety of AI‑generated responses across defined use cases. This role combines hands‑on human review with structured, rubric‑based evaluation incorporating automation to ensure AI systems meet documented standards before customer implementations go live.
As part of the implementation team, this role is client-facing and serves as a bridge between client expectations and system behavior, translating real-world use cases, domain context, and risk tolerance into measurable evaluation criteria and actionable feedback for product and engineering teams.
The role focuses on what the AI says and does, not on model training or infrastructure performance. The analyst serves as a human quality gate, ensuring outputs are accurate, appropriate for the audience, and aligned with policy and governance requirements.
This role works closely with product and domain experts to translate real‑world expectations into measurable evaluation criteria and repeatable test artifacts.
What Your Impact Will Look Like
Posted June 26, 2026