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# Senior/Staff Software Engineer

- **Company:** Looma LLC
- **Location:** Durham, NC, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Databases, Continuous Integration, Software Debugging, PostgreSQL, Redis, Systems Integration, Google Cloud, Concurrency, Technical Debt, Backend, AngularJS, Integration Tests, Front End Software Development, Marketplace, Data Pipelines, Microservices
- **Published:** September 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=28117518c6de3989

## About the Role

* You have independently built and shipped a meaningful production software product in a small, ambiguous environment.
 * You have materially raised the engineering quality of an existing production codebase while continuing to ship features.
 * You bring high ownership and bias to action, strong product judgment and user empathy, technical curiosity, humility, and a willingness to speak up.
 * You are deeply AI-native: you routinely delegate implementation to coding agents and build verification loops that produce sound outcomes.
 * You make pragmatic speed-versus-quality calls, raising standards without using perfection as a reason to stop shipping.

## Description

Looma is seeking a Senior or Staff Software Engineer to help turn Looma's Marketplace product into indispensable software for advertisers and retailers. We are open to leveling this role based on experience, demonstrated scope, and expected impact. You will join a small product team and take ambiguous business problems from discovery through production, working backend-first while contributing across the web stack. This role is for a product-minded builder who moves quickly with little hand-holding, uses AI coding agents effectively, and raises the engineering bar without sacrificing speed. You will help evolve a conventional API-and-database backend toward more scalable async workflows, queues, concurrency, intelligent caching, and clearer service boundaries-without prematurely forcing a microservices architecture. Our current stack includes GCP, Go services, BigQuery, Postgres, Redis, and Angular; experience with every tool is not required, and strong engineers should be able to
learn quickly.

The responsibilities for this role can be split into three primary categories:

 * Marketplace product delivery: 55%

 * Engineering quality and architecture: 25%

 * Integrations, data, internal tooling, and emerging needs: 20%

Marketplace product delivery (55%)

 * Own and ship Looma Marketplace features end-to-end, translating advertiser, retailer, and internal business needs into useful production software.
 * Work backend-first across Go services, GCP, Postgres, Redis, and BigQuery while contributing comfortably to the Angular frontend when needed.
 * Partner closely with a Product Manager, Product Designer, and long-tenured backend engineer to turn ambiguity into clear decisions and shipped software.
 * Move quickly, learn from production, and correct course without losing sight of craftsmanship or the people using the product. Success means increasing the team's rate of reliably shipping high-quality software for stakeholders.

Engineering quality and architecture (25%)

 * Evolve the backend beyond a conventional API-and-database architecture with asynchronous workflows, queues, concurrency, intelligent caching, and clearer service boundaries.
 * Improve branch protections, branch naming, CI/CD consistency, automated integration testing, observability, and system-performance dashboards.
 * Make pragmatic code-review and remediation decisions: rewrite to demonstrate a better path, coach, or establish reusable standards and automation.
 * Keep velocity high while paying down the technical debt that most constrains delivery and reliability.

Integrations, data, internal tooling, and emerging needs (20%)

 * Own integrations, data pipelines, infrastructure, and internal tooling that support Marketplace and adjacent business needs.
 * Debug cross-system failures and build pragmatic tooling or automation that makes the team faster and more dependable.
 * Apply AI-assisted engineering workflows with clear plans, review gates, testing, and other verification mechanisms.
 * Contribute across repositories and problem domains when a business priority needs engineering leverage.