Software Engineer 4, AI-Native

Granicus•Remote,

4d•$88,000 - $180,000•Remote

About The Position

Granicus is seeking an AI-Native Software Engineer 4 to join the Office of the CTO. This role is part of an AI-native software development lifecycle where autonomous agents perform high-confidence implementation work, and senior engineers orchestrate, review, and own the outcome. The engineering standards are aligned with leading software and AI organizations, including generator-verifier architecture, eval-driven development, staged deployment, and high-volume autonomous pull-request pipelines, all within a FedRAMP-authorized environment. This position is for a senior engineer who can direct coding agents, rigorously review agent-generated code, and ship production code in a regulated environment. The role contributes to defining how engineers operate in an AI-native lifecycle, not just adopting AI tooling. Compliance obligations such as NIST 800-53 Rev 5, WCAG, SOC 2, and FedRAMP authorizations are treated as engineering requirements.

Requirements

Strong engineering fundamentals. Data structures, systems design, and testing, with the ability to read unfamiliar code quickly and assess it accurately.
A record of shipping production software you owned the quality of, including responsibility for diagnosis and remediation when it failed.
Hands-on experience directing coding agents on production work, including their failure modes and the practice of reviewing agent-generated code critically rather than approving it by default.
Demonstrated code-review competence. You identify defects that automated tests do not catch, provide actionable feedback, and maintain a high bar without becoming a bottleneck.
High autonomy. You advance work without step-by-step direction and escalate issues proactively.

Nice To Haves

High-assurance or regulated experience. Shipping within FedRAMP, defense, financial services, healthcare, or another NIST 800-53 / SOC 2 / HIPAA-bound environment.
Depth in evaluation authoring or test-first development within a rigorous engineering culture.
Full-stack range, sufficient to review front-end and back-end agent output with equal confidence.
Public-sector or govtech experience and familiarity with the relevant end users.

Responsibilities

Direct the agent array on production workstreams — decompose problems into tasks suitable for agent execution, dispatch them, and integrate the output into shipped software.
Review agent-generated pull requests at volume and at depth — identify correctness, security, and accessibility defects that automated tests do not catch, while maintaining review throughput and a consistent quality bar.
Author evaluation suites that make quality measurable — define criteria under which the pipeline validates correctness rather than relying on subjective assessment. Eval-driven development is your standard practice.
Own quality end to end — correctness, performance, security posture, and WCAG accessibility of the software your team ships, irrespective of which component or agent produced the initial implementation.
Advance workstreams along the autonomy ladder on the basis of evidence — move work from supervised to autonomous execution when measured reliability supports it, and revert promptly when it does not.
Strengthen the development lifecycle itself — identify where patterns, prompts, or pipeline components degrade at volume and work with the lead architect to remediate them.
Maintain agent operations within the security boundary — branch-only execution, vaulted credentials, sandboxed actions, and in-VPC inference. Throughput does not justify exceptions.