Product Engineer III

About the Role

OpenGov is hiring a Product Engineer to own a domain inside our ERP — the financial system of record for state and local government. You will own a product area end to end: customer discovery, the roadmap, the user experience, the build, the launch, and the adoption number. This is a new kind of role, born from AI's ability to handle execution work that once required three specialists. What AI cannot do is decide what matters, sit with a finance director through a budget cycle, make the right call in an ambiguous compliance question, or own whether a product succeeds. That is what Product Engineers do.

The Domain

ERP at OpenGov is a suite, and this role owns a domain within it. Depending on fit, that domain sits in or across:

• Financial Management — general ledger and the chart of accounts, accounts payable, accounts receivable and cash receipts, fixed assets, purchase card, requisitions, bank reconciliation, project accounting.

• Budgeting & Performance — budget creation and proposals on the ERP chart of accounts, worksheets, multi-period adoption, amendments and transfers, workforce planning, performance measures.

• Reporting & Financial Statements — the financial report engine, multi-hierarchy and multi-entity reporting, GASB-compliant statements, the datasets and pipelines beneath them, and the transparency surfaces governments publish to residents.

• Procurement — intake through solicitation, evaluation, award, and contract management, and the vendor record that connects procurement to AP.

What You'll Own

• A domain. A defined set of customers, problems, and measurable business outcomes you are accountable for driving. You are the DRI — the directly responsible individual — for all things product in that domain.

• The roadmap. What gets built, in what order, and why, informed by customer research, competitive context, and business goals. You set it, defend it publicly, and update it when new facts warrant it. Aha and the Roadmap Portal stay the source of truth so GTM can work from it.

• The end-to-end user experience. From first interaction to last, you define the flow and validate the design within the design system — not just the requirements.

• The ship. From idea to live in customers' hands. You drive intent, design, build coordination, launch, and iteration without handing off across three roles. Engineers review your PRs the way they review each other's.

• The number. Adoption, go-live and retention targets, and the revenue tied to your domain. The outcome belongs to you.

• Field time. Product Engineers are members of Customer Product Squads alongside an Engagement Lead and a Solution Architect, and stay on accounts after go-live. Expect roughly 20–25 hours per implementation — concentrated in discovery, with lighter oversight through configuration and training — capped at about a quarter of your time. The other three quarters is your domain. When a bug surfaces on site, you fix it on site rather than filing a ticket and waiting.

How AI Works in This Role

AI-native tooling handles a significant portion of what product managers and UX designers historically spent their time on. That time is yours to redirect toward higher-leverage work.

• Spec writing. The prototype is the spec. You build first, in the product repo, with AI skills that carry our standards; the product brief is generated from what you built. Nobody writes a PRD first.

• UX design. AI generates screens from the design system based on your flow definitions, and design-review agents sanity-check what you built. You make the product decisions within the system and escalate genuinely new patterns.

• Research synthesis. AI clusters and themes interview notes, call transcripts, support cases, and product usage. You interpret what it means for the roadmap and make the call.

• Release content. AI drafts release notes, in-app announcements, demo data, and enablement material from what you shipped.

• Code review and test coverage. Automated review catches style, security, and regression issues; AI generates test cases from your acceptance criteria. You stay accountable for quality outcomes, and your acceptance criteria have to be precise enough to verify.

• Competitive and regulatory monitoring. AI surfaces competitor moves and changes in accounting standards and state reporting requirements. You form the point of view and decide what it means for the roadmap.

What AI does not do: understand your customers, make the call on what matters, own the outcome, or build the cross-functional trust that makes things ship. That is the job.

You are also expected to improve the tooling itself — identify gaps in AI harnesses, skills, and design system coverage, and surface them as platform investment requests with a clear business case.

Key Responsibilities

• Define and communicate the product vision for your domain, grounded in customer research, competitive context, and business goals — not inherited from committee.

• Conduct and synthesize discovery with government finance staff: translate what you hear into clear, defensible decisions about what to build and what to cut.

• Own the roadmap: prioritize ruthlessly, explain your reasoning publicly, and revise it when new facts warrant it.

• Define user experience flows and interaction patterns within the design system; escalate to platform and design when a genuinely new system-level pattern is required.

• Build. Use AI-native tooling to move from intent to working software in the product repo, validate with customers, and iterate. Own your PRs through review.

• Write acceptance criteria precise enough for automated tests to verify, and treat quality as a pipeline property rather than a hardening phase.

• Partner with engineering leads and squad engineers to unblock builds and resolve ambiguity in real time without becoming a bottleneck.

• Embed with Professional Services on implementations and migrations: run discovery, close the gap between what the product does and what the customer configured, and feed what you learn straight back into the roadmap.

• Track adoption, usage, go-live health, and business outcomes; use them to drive the next iteration, not just to report status.

• Represent your domain in customer conversations, QBRs, steering committees, and cross-functional reviews — the full commercial picture, not just the feature set.

• Coordinate directly with adjacent domains when a customer need spans more than one, and bring a recommendation rather than a question.

Core Skill Sets — Non-Negotiables

Ranked in order of importance and impact. The first three are the screen; the rest are the bar.

• Ownership under ambiguity. You make good decisions with incomplete information and iterate faster than you wait for certainty. One DRI means there is nobody else to point to, and that energizes you rather than worrying you. Candidates who have only operated inside a PM-designer-engineer trio, with someone else accountable for the outcome, will struggle here.

• Demonstrated product ownership with a track record. Product management, product design, or a closely adjacent role, where you shipped things customers actually use and can point precisely to what you owned versus what the team owned. This is an individual-contributor role, not a management one.

• Depth in a complex, workflow-heavy, compliance-bound B2B domain. Financial software, ERP, accounting, or a comparably regulated enterprise domain. The general requirement is that you have owned a product where being wrong had consequences beyond a churned subscription.

• Customer discovery you have actually run. You have conducted discovery, synthesized the research yourself, and changed a roadmap or a design because of what you learned — with a specific example.

• Written communication. You can articulate a product decision clearly enough that engineering, design, services, and leadership all walk away aligned, without a follow-up meeting. Expect a writing signal in the process.

• Willingness to build. You do not need to arrive as a developer, but code fluency has to read to you as a career accelerator rather than a threat. Experience in AI-native workflows is a plus; willingness to become proficient in them is required.