About the Role

Community Intelligence is a new engineering team at OpenGov, based in our Boston office, chartered with bringing next-generation physical-world sensing and AI-based detection into our Community Operations suite. Rather than treating sensing as an external add-on, this team builds the pipeline and integration layer that make it a native, foundational capability across our products.

As a founding Staff Software Engineer on this team, you will design and build the systems that turn raw sensor data into structured records, condition assessments, and automated workflows across multiple products. You will make real technical calls with incomplete information, evaluating emerging sensing technologies, reconciling third-party data against our own systems, and sequencing a rollout across a multi-product suite. You will also set patterns the rest of the team builds on. AI-native tooling is expected to be embedded in your workflow.

What You'll Own

• Design and build the sensing-platform connector/adapter layer that maps LiDAR- and imagery-derived asset detections into OpenGov Products

• Architect the automated detection-to-case pipeline that turns a sensing detection into a properly routed record in the right product's workflow engine, complete with photo evidence, GPS coordinates, and a severity score.

• Evaluate, integrate, or build the computer-vision and LiDAR-fusion models this requires, including the technical path for consolidating with or extending EAM's existing Vision AI microservice (rd-capture).

• Design the data model and storage layer for a continuously updated spatial data that all five Community Operations products read from and contribute to.

• Own the technical design for a tiered sensing-ingestion model (satellite, fleet-vehicle camera, full LiDAR survey) supporting different refresh cadences, accuracy levels, and price points.

• Partner with engineering and product leads across OpenGov products to sequence the sensing layer's roadmap against each product's asset taxonomy and compliance requirements.

• Write clear technical design docs that AI tooling can execute against; review and own AI-generated code for correctness, security, and architectural fit.

• Establish testing, monitoring, and data-quality standards appropriate to a system whose outputs feed regulatory and safety-relevant workflows, including ADA compliance and FEMA reimbursement documentation.

Qualifications & Preferred Experience

• 12+ years of software engineering experience, with a track record of owning complex, cross-system integrations end-to-end in a production SaaS environment.

• Experience building or integrating computer-vision, LiDAR, or geospatial data-processing pipelines; comfort with point-cloud or 3D spatial data is a strong plus.

• Strong data-modeling and API/connector design skills, able to reconcile a third party's data schema against multiple existing internal data models without resorting to one-off custom logic.

• Experience with geospatial systems (PostGIS, spatial indexing, coordinate reference systems) preferred.

• Comfortable operating with incomplete information and ambiguous vendor integration paths; makes and defends build-vs-integrate calls.

• Experience partnering across multiple product teams and translating a strategic technical vision into a scoped, sequenced delivery plan.

• A track record of shipping systems where data accuracy carries real compliance or safety consequences (regulatory, infrastructure, or public-sector systems) is a strong plus.

• Proficient in AI-native engineering workflows: can direct AI tooling for scaffolding, test generation, and code review while retaining ownership of architecture and correctness.

• Excellent written communication; can produce technical design docs that align stakeholders across five product teams.

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

How This Level Is Differentiated

The following competency behaviors distinguish this level from adjacent ones:

• Owns a technical domain end-to-end with full accountability for outcomes, from architecture through production operation.

• Operates with strategic awareness across multiple downstream product teams; makes strong technical calls with incomplete vendor and data information.

• Sets technical direction and milestones for the sensing-integration roadmap; influences cross-functional partners without formal authority.

• Establishes patterns, like the connector/adapter approach, that other engineers and products reuse, elevating the work of the broader team.

• Expected to embed AI-native tooling in their own workflow and model its effective use for teammates joining the team.

Why OpenGov?

• Comprehensive healthcare options for individuals and families

• Flexible vacation policy and paid company holidays

• 401(k) with company match

• Professional development and growth opportunities