Staff Software Engineer, Core

Madison Reed•San Francisco, CA

10h•$170,000 - $175,000•Remote

About The Position

The Staff Software Engineer on the Core team is a unique and vital role within Madison Reed, owning the foundational platform that nearly every other system at the company is built on. This role owns the backend services, APIs, data models, and integrations that power the entire business. It involves architecting and leading the development of the systems other teams depend on, driving technical strategy for the platform, and contributing to the organization’s long-term architectural vision. Working in a cross-functional, agile ai-first environment, the engineer collaborates with teammates, product owners, and stakeholders across every line of business, while mentoring engineers at all levels and fostering a culture of innovation, collaboration, and excellence. We expect our Staff Software Engineer to both build and use the AI capabilities and infrastructure that other teams build on top of, and to have fundamentally changed how they build by working alongside frontier agentic coding tools, while retaining the deep technical ownership required to audit, verify, and own everything that ships

Requirements

8+ years of professional software engineering experience, with deep expertise building production backend systems in JavaScript/TypeScript (Node.js) and the surrounding service ecosystem.
A proven track record of designing, shipping, and maintaining complex, data-heavy, high-throughput platforms in production at scale.
Platform and systems architecture mastery. You design APIs, data models, and service boundaries that hold up as multiple teams build on them, and you reason fluently about scalability, consistency, and failure modes.
Secure and reliable by default. Deep understanding of secure coding practices, data integrity, performance optimization, and the observability and debugging tools needed to operate critical systems in production.
Full lifecycle ownership. You build things that run reliably in production, not just pass review, owning the CI/CD pipeline, error rates, and your services’ behavior under real-world load.
Your workflow has been altered by AI. You are already using frontier agentic coding tools (e.g. Claude Code, Codex, Cursor) to build faster, and can describe specific ways they have structurally changed how you work, while retaining the technical curiosity and ownership to audit, verify, and fully own their output.
Demonstrated technical leadership. A track record of setting technical direction across teams, designing scalable and maintainable architecture, and measurably leveling up the engineers around you.
A high-ownership mindset with a bias toward action, comfort operating in ambiguity, and the ability to balance technical and business considerations in complex, high-pressure situations.
Experience building or operating the AI/LLM infrastructure that other engineering teams build on (agent frameworks, eval pipelines, retrieval/RAG, prompt and tool-call tooling).
Exceptional communication and collaboration skills, with low ego and high standards.

Nice To Haves

Background in e-commerce, subscriptions/memberships, payments, fulfillment, or order management systems.
Experience decomposing a monolith, or evolving a core platform that many teams depend on, without breaking them.
Experience with event-driven architectures, data pipelines, or third-party systems integration.
Open-source contributions, or platforms you’ve built and shipped yourself.

Responsibilities

Own the core platform end-to-end. Architect, build, and ship the services, APIs, and data models at the heart of Madison Reed, making foundational decisions that every other team depends on.
Drive platform technical strategy. Identify opportunities for innovation and lead the adoption of new technologies, tools, and patterns. Set the standards and contracts that keep a multi-team, multi-domain platform coherent as it scales.
Build the AI foundation for the company. Stand up the infrastructure, services, and patterns that let every team integrate LLMs and agents safely, and bring AI capabilities directly into core business workflows.
Engineer for scale, reliability, and security. Treat performance, observability, data integrity, and secure coding as first-class concerns. Design systems that are resilient, debuggable, and safe by default.
Own the contracts other teams build on. Design clean, well-versioned APIs and integrations; anticipate how downstream teams will use them; and treat backward compatibility and developer experience as part of the product.
Own reliability in the wild. Treat CI/CD, monitoring, and incident response as a fundamental part of the job, not an afterthought. Set a high bar through observability, error tracking, and optimization across the systems the whole business runs on.
Take ownership of large, ambiguous initiatives and break them into actionable workstreams across multiple teams. Lead efforts to refactor and optimize large areas of the codebase, ensuring alignment with business goals and long-term scalability.
Mentor and raise the bar. Establish patterns for code reuse, elevate the engineers around you through rigorous code review and testing practices, and foster a culture of technical excellence and knowledge sharing.
Collaborate with product and leadership across every line of business to align technical solutions with business priorities, shaping both what gets built and how it gets built.