Software Engineer, Enterprise Frameworks

Staff Software Engineer, Enterprise Frameworks

Reno, NV;
San Ramon, CA

Are you a seasoned engineer with a passion for building extensible, scalable platform frameworks? Do you enjoy designing systems that other engineering teams build on top of and guiding teams through technical complexity? Are you energized by ambiguous architecture challenges, iterative problem solving, and strengthening the foundations of an enterprise platform? If so, we invite you to be a part of our innovative team.

As a Staff Software Engineer on Ridgeline's Enterprise Frameworks team, you will help design and evolve foundational platform capabilities that product engineering teams build on top of every day. Today, this includes frameworks such as Search, Audit Trail, and Custom Fields; over time, the team's scope will expand as new shared capabilities emerge across the platform. This role requires strong software architecture judgment, creative iterative thinking, and the ability to turn ambiguous product and platform needs into scalable, extensible systems.

You'll help teams design data models, APIs, and event-driven workflows, making practical tradeoffs and building systems that can grow with Ridgeline. You'll collaborate closely with Platform, Product, and other engineering teams across Ridgeline to solve high-impact challenges using modern technologies, including AI tools like Claude Code and ChatGPT.

At Ridgeline, how we work matters as much as what we build. Ridgeliners act like owners, choose growth over comfort, and communicate with transparency. We assume positive intent, bias toward action, and bring solutions—not just problems. We celebrate wins, learn from setbacks, and thrive in a resilient, collaborative, high-performing culture. If the Ridgeline Way excites you, we'd love to meet you.

You must be work authorized in the United States without the need for employer sponsorship.

The impact you will have:

• Design, build, and evolve extensible enterprise platform frameworks that enable product teams to add configurable, searchable, auditable, and operationally reliable capabilities to their applications.
• Lead architecture discussions for shared infrastructure, including data models, APIs, event-driven workflows, indexing pipelines, background jobs, and operational patterns.
• Apply creative, iterative problem solving to ambiguous technical challenges, balancing long-term platform direction with short-term delivery needs.
• Design and test durable platform abstractions with strong attention to correctness, performance, scalability, security, data integrity, and developer experience.
• Use AI tools thoughtfully throughout the SDLC to accelerate research, prototyping, implementation, testing, documentation, and review, while ensuring outputs are accurate, secure, maintainable, and production-ready.
• Participate in on-call rotations and production support for the team's services.
• Be involved in the entire software development process, including requirements and design, implementation, code reviews, automation, testing, and end product delivery.
• Help evolve Ridgeline's cloud-backed platform with attention to operability, scalability, security, and cost-efficient infrastructure choices.
• Coach, mentor, and inspire engineers across teams on architecture, design tradeoffs, reliability, scalability, and maintainability.
• Proactively collaborate across Platform, Product, other engineering teams, and cross-functional partners to establish partnerships and champion innovation

What we look for:

• 8+ years of software engineering experience, with a track record of architecting and delivering shared platforms, infrastructure, or frameworks used by multiple engineering teams.
• Strong software architecture judgment, including the ability to decompose ambiguous problems, compare design alternatives, make pragmatic tradeoffs, and evolve systems iteratively.
• Experience designing extensible data models, APIs, and platform abstractions that support changing business requirements without sacrificing correctness, performance, or maintainability.
• Experience with distributed systems patterns such as event-driven workflows, asynchronous processing, fan-out jobs,…