Full-Stack Product Engineer

The role

Full-stack product engineers will own ambiguous customer or internal problems from discovery to production. You will build vertical slices across the stack including frontend, backend, data, testing, and observability.

What you will do

• Own ambiguous customer or internal-team problems from discovery through measurable production outcomes
• Build coherent vertical slices across frontend, backend, workflow state, data, testing, observability, security, and release
• Make complicated processes clear without hiding exceptions, uncertainty, or recovery paths
• Diagnose difficult production behavior and remove recurring root causes
• Establish useful measurements and improve customer, team, quality, or reliability outcomes
• Create reusable product and engineering capabilities
• Use AI deeply in development and where it improves the product
• Work directly with Product, Design, customers, domain experts, and other engineers

Required qualifications

• At least three years of professional software engineering experience
• Strong full-stack engineer with excellent product and UX judgment
• Experience working in a startup
• Experience owning ambiguous problems from discovery through implementation, production operation, and iteration
• Ability to make complex workflows clear while reasoning about state, data integrity, testing, security, observability, and recovery
• Ability to use evidence to debug systems and measure outcomes
• Fluency in using modern AI engineering tools and verifying their output
• Clear communication across technical and customer-facing teams

Nice to have

• Strong TypeScript, React, Node.js, or comparable full-stack experience
• Experience with integration-heavy SaaS, APIs, OAuth, uploads, files, or asynchronous workflows
• Experience with document workflows, internal tools, evaluation systems, data quality, or production diagnosis
• Experience building high-fidelity, resettable simulation or evaluation environments using synthetic data, seeded failure modes, multi-step state, and programmatic verifiers
• Experience with multi-tenant, compliance-sensitive, or otherwise high-trust products
• Experience shipping trustworthy AI-assisted workflows

About the company

Replay is building the first-ever bank for enterprise data to help businesses monetize historical operating data by licensing it to AI and data labs. The company has scaled to a multi-eight-figure run rate and is backed by investors including Floodgate, Afore, Ludlow, and Hustle Fund.