Lead Integrations Engineer

As Lead Engineer on our Integrations team, you will own the technical direction for how One App connects with external property management platforms and delivers data across our ecosystem. You will set the integration patterns the team builds against, lead a small team of engineers, and work alongside a specialist AI engineer on automation and data collection workflows. This is a hands‑on technical lead role.

You write code, you review code, and you are accountable for what the pod ships. Your primary focus will be integration architecture and delivery. The secondary focus is data pipeline design, external API surface, and team technical leadership. This role is a hybrid schedule, with some in‑office time at our Portland, OR location.

• Design and implement the integration patterns that connect One App with third‑party property management systems — establishing reusable architecture so each new integration builds on proven foundations rather than starting from scratch
• Own the full integration lifecycle — API access, data ingestion, transformation, and delivery to downstream systems — with a focus on reliability, data quality, and maintainability
• Build and maintain the external‑facing Partner Data API — including authentication, rate limiting, versioning, and the developer experience for partners consuming it
• Treat data quality as an engineering discipline — data that enters incorrectly causes downstream problems; you design the layer to catch and handle issues at the source
• Ensure integrations are observable by default — logging, alerting, and monitoring are part of implementation, not an afterthought Agentic AI — Technical Fluency Required
• You will work alongside a specialist AI engineer who drives the agentic AI implementation. You need to be technically fluent enough to provide architectural direction, make good decisions about where automation belongs in the integration stack, and hold the engineering standard — even if you are not writing the agent code day to day.
• Understand agentic AI architectures well enough to make sound decisions about where agents belong and where they do not
• Provide technical oversight of AI‑powered workflows — automated data collection, enrichment pipelines, and intelligent data retrieval
• Evaluate AI frameworks and tooling in the context of production reliability and observability, not just capability
• Hold the engineering standard: AI‑powered workflows should be observable, testable, and as reliable as any other production system

• Set and enforce technical standards for the pod — code quality, API design, data contracts, and integration patterns
• Lead architecture discussions and represent the integration team's perspective in cross‑team technical conversations
• Create an environment where the engineers around you can do their best work — clear direction, substantive code reviews, and space for ownership
• Unblock the team proactively — if a third‑party API is unclear or a dependency is missing, you chase it down
• Document integration patterns and architectural decisions so the team’s knowledge is shared and durable

• 5+ years of software engineering experience in production environments, with at least some experience leading technical work or mentoring engineers
• Strong, hands‑on proficiency in Type Script
• Experience building and maintaining production integrations with third‑party APIs — authentication, pagination, rate limiting, error handling, and the operational reality of external dependencies
• Experience designing data pipelines and transformation layers — you know what it means to move data reliably from an external source through your system to a consumer
• Solid understanding of RESTful API design,…