Staff Software Engineer

Storable is redefining property management for specialty real estate, and they are seeking a Staff Software Engineer to help shape the next chapter of their Edge platform. This role involves both deep technical contributions and collaborative leadership to enhance the platform's reliability and scalability while integrating AI-assisted development practices.

Responsibilities:

• Shape the technical direction for the Edge domain by guiding the evolution of our Rails monolith, Postgres data layer, and supporting infrastructure (Sidekiq, Redis, Kafka, AWS) toward a more modular, resilient architecture
• Own the technical direction and strategy for key projects, ensuring alignment with broader business goals and influencing product roadmaps and long-term planning
• Define pragmatic, well-communicated tradeoffs around performance, reliability, and delivery that help teams and stakeholders make informed decisions
• Establish and refine engineering patterns and standards (testing, observability, deployment, code quality) that raise the bar across Edge teams
• Help define and scale AI-augmented engineering practices across the organization, including coding assistants, automated testing, code review, incident analysis, and agentic development workflows
• Partner with Product Management, Payments, Data Platform, DevOps, and adjacent teams to shape requirements, define APIs and integration contracts, and align on shared priorities
• Break down large technical initiatives into clear milestones and increments, helping teams deliver them safely and predictably
• Provide clear technical context, risks, and options to leadership to support roadmap and capacity decisions
• Facilitate alignment across teams by building shared understanding and trust
• Advocate for reliability and correctness in high-risk areas (payments, reporting, financials, delinquency, nightly jobs) through thoughtful design, testing strategy, and runtime safeguards
• Contribute to and help facilitate post-incident reviews, turning RCAs into concrete engineering and process improvements
• Strengthen observability and on-call practices so teams can detect, diagnose, and resolve issues with confidence
• Contribute high-quality, production-ready code in our stack (primarily Ruby on Rails, Postgres, Sidekiq, Redis, AWS) and review critical changes, focusing your hands-on time where your expertise has the greatest leverage
• Step into complex performance and reliability problems when the situation calls for your depth of experience, whether that means identifying hotspots, optimizing queries, or simplifying code paths
• Model engineering excellence through targeted contributions that set the standard for the team
• Evaluate, prototype, and operationalize AI-assisted development approaches that improve engineering velocity, quality, and reliability
• Mentor Senior Engineers and new Staff Engineers, helping them grow their technical judgment, expand their influence, and take on greater ownership
• Foster a culture of continuous improvement by encouraging better approaches to testing, automation, deployment, and collaboration (including thoughtful adoption of AI-assisted development tools)
• Serve as a trusted resource for the Edge stack and domain, modeling how to navigate ambiguity, weigh tradeoffs, and communicate clearly across audiences

Requirements:

• 8+ years of professional software engineering experience, with substantial time in SaaS or product engineering environments
• 3+ years operating at a Staff, Principal, or Lead level (or equivalent scope), including owning architecture, guiding delivery for complex systems, and mentoring other senior engineers
• Demonstrated experience evolving a large, mature codebase (ideally a Rails monolith) toward a more modular, scalable architecture
• Deep proficiency in a modern server-side framework (Ruby on Rails) and relational databases (Postgres or MySQL), including schema design, indexing, query optimization, and scaling patterns
• Solid understanding of distributed systems concepts and event-driven architectures (background jobs, queues, events/streams)
• Strong foundation in testing, CI/CD, observability, and incident response in production environments
• Ability to reason about performance, reliability, and data correctness in financial or similarly sensitive domains
• Comfortable using AI-assisted development tools in your daily workflow and eager to help teams adopt effective AI-augmented engineering practices
• Experience shaping AI-augmented engineering workflows for teams (e.g., multi-agent setups for implementation, test generation, refactoring, or incident analysis)
• Demonstrated experience driving adoption of AI-assisted software development practices across engineering teams
• Experience evaluating and implementing AI-augmented workflows such as agent-based development, automated test generation, code migration/refactoring, documentation generation, or incident analysis
• Ability to articulate measurable impact from AI adoption on engineering productivity, quality, or delivery
• A track record of setting technical direction for a domain and building alignment across teams through clear communication and shared understanding
• Experience partnering closely with Product, Design, and cross-functional stakeholders to shape scope, requirements, and delivery plans
• A demonstrated pattern of investing in other engineers' growth and making the people around you more effective
• Experience operating and scaling high-throughput, transaction-heavy SaaS systems using tools like Sidekiq, Postgres/RDS, Redis, Kafka/MSK, and AWS
• Background in payments, accounting/ledger systems, or other high-integrity financial domains
• Experience improving test suites and deployment practices (e.g., reducing test runtime, eliminating flaky tests, introducing canary or blue/green deploys)
• Familiarity with self-storage, property management, or similar operational software domains