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Granicus connects governments with the people they serve by providing the first and only civic engagement platform for the public sector. Over 5,500 federal, state, and local government agencies and more than 300 million citizen subscribers power an unmatched Subscriber Network that turns government missions into quantifiable results. 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.
Granicus serves more than 7,000 public-sector agencies and powers approximately 30 billion digital interactions annually. Within the Office of the CTO, we operate an AI-native software development lifecycle: a production engineering model in which autonomous agents perform high-confidence implementation work and senior engineers orchestrate, review, and own the outcome. The model is established and operating; we are scaling it across additional delivery teams.

This role joins one of those teams. Our engineering standards are calibrated to the practices used by leading software and AI organizations - generator-verifier architecture, eval-driven development, staged deployment, and high-volume autonomous pull-request pipelines - operated within a FedRAMP-authorized environment. We are hiring practitioners who will set and uphold these standards, not engineers who simply use AI tooling.

Operating constraints (non-negotiable): agents execute only within branches; all agent-generated code passes senior human review before merging to production; autonomous execution is a force multiplier and does not transfer accountability away from the responsible engineer. Compliance obligations - NIST 800-53 Rev 5, WCAG, SOC 2, and applicable FedRAMP authorizations - are treated as engineering requirements and a source of competitive advantage.

Why this role exists

High-volume autonomous agent pipelines are straightforward to demonstrate and difficult to operate safely, performantly, and auditably at scale. This role owns that problem. It is responsible for the generator-verifier architecture, agent orchestration patterns, the eval-driven development discipline, and a continuous integration and delivery system engineered for a high volume of autonomous agent pull requests - all within a security boundary that keeps model inference inside the VPC (AWS Bedrock) and sandboxes agent actions (WASM-isolated runtime with encrypted credential storage). The role sets the engineering standards inherited by every delivery team and is the final human accountability gate before agent-generated code merges to productio

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