Staff Software Engineer, Enterprise Frameworks

Ridgeline•Reno, NV

4h•$200,500 - $251,000•Hybrid

About The Position

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.

Requirements

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, caching, idempotency, consistency models, observability, and failure handling.
Experience designing data-intensive systems such as search indexing, audit/event pipelines, background jobs, metadata frameworks, or distributed processing workflows.
Strong backend engineering experience with object-oriented languages such as Java, Kotlin, or Python, and relational databases such as PostgreSQL.
Experience operating production services, including monitoring, alerting, logging, incident response, performance tuning, scalability, and data integrity.
Experience managing large or distributed codebases and working effectively in agile development environments with tools such as JIRA.
Strong knowledge of data structures, algorithms, architectural patterns, and secure software development practices.
Ability to focus on short-term deliverables while maintaining a big-picture perspective.
Ability to mentor engineers, influence technical direction across teams, communicate clearly with technical and cross-functional partners, and bring a serious interest in having fun at work.

Nice To Haves

Experience with AI-assisted development workflows, including tools such as Claude, Cursor, Copilot, or similar.
Hands-on expertise with Kafka, Redis, or similar messaging, event-streaming, or caching technologies.
Hands-on expertise with Kubernetes, Helm, or similar service deployment and orchestration tooling.
Experience with Spark or other distributed processing frameworks.
Understanding of AWS back-end infrastructure, especially RDS, Lambda, and related managed services.
Working knowledge in JavaScript, React, HTML, CSS.
Familiarity with cloud-based multi-region application architectures.
Experience with testing frameworks such as Jest, Pytest, and Cypress.
Experience developing mission-critical enterprise software applications.
Familiarity with search relevance/ranking or compliance and audit requirements, such as SOC 2, in regulated industries such as financial services.

Responsibilities

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.