Product Engineer

OpenGov•Boston, MA

63d•$110,000 - $125,000•Hybrid

About The Position

OpenGov is seeking a Product Engineer II to take on increasing ownership of a product area with cross-functional exposure. This role is for developing practitioners who can contribute to discovery, roadmap input, and delivery with general direction from a lead, while growing their ability to operate independently. AI-native tooling accelerates execution — your job is to direct it toward the right outcomes for customers. AI-native tooling handles a significant portion of what product managers and UX designers have historically spent their time on. That time is yours to redirect toward higher-leverage work. Specifically: Spec writing: AI drafts the first spec from your intent statement. You review, sharpen, and own what gets built. UX design: AI generates mockups from the design system based on your flow definitions. Experience Architects maintain the system itself. You make the product decisions within it. Research synthesis: AI clusters and themes interview notes, call transcripts, and support data. You interpret what it means for the roadmap and make the call. Release content: AI generates release notes, in-app announcements, and enablement materials from your shipped features. Code review: Automated review catches style, security, and regression issues. You stay accountable for quality outcomes — not the review queue. Test coverage: AI generates test cases from the acceptance criteria you write. Your job is to write criteria that are precise enough to verify. Competitive intelligence: AI monitors competitor moves and surfaces market signals. You form the point of view and decide what it means for your 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.

Requirements

2–4 years of experience in product management, software engineering, or a closely adjacent technical role.
Ability to contribute to and navigate cross-functional engineering projects, with awareness of how your work connects to system architecture and broader team goals.
Experience conducting customer or stakeholder interviews, or translating technical requirements and user research into actionable engineering specs.
Solid written and verbal communication; can explain technical tradeoffs clearly, provide project updates, and incorporate feedback at key milestones.
Adapts to changing priorities and demonstrates a track record of shipping reliably.
Developing comfort with AI-assisted development workflows (e.g., AI-assisted coding, code review, or testing tools); willingness to become proficient is required.

Nice To Haves

Familiarity with design systems, component-based architecture, or API/data modeling is a plus.
Experience with modern SaaS architecture (APIs, cloud infrastructure, CI/CD) preferred.

Responsibilities

Define and communicate the product vision for your area — grounded in customer research, competitive context, and business goals; not inherited from committee.
Conduct and synthesize customer discovery: translate what you hear into clear, defensible decisions about what to build and what to cut.
Own the product 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 Experience Architects when genuinely new system-level patterns are required.
Write clear intent documents that AI tooling can execute against; review and own AI-generated specs for accuracy, completeness, and correctness.
Partner with engineering to unblock builds, resolve ambiguity in real time, and make decisions during the development cycle without becoming a bottleneck.
Track adoption, usage, and business outcome metrics; use them to drive the next iteration, not just to report status.
Represent your product in customer conversations, QBRs, and cross-functional reviews — the full commercial picture, not just the feature set.
Identify gaps in AI harnesses and design system coverage; surface them as platform investment requests with clear business justification.