stable - Product Engineer
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Requirements
• Skills needed: Experience with frontend/backend development, hardware integration, internal software for intake, routing, fulfilling customer requests. Familiarity with AI and ML models to route mail, classify documents, extract data, trigger workflows is a plus but not mandatory as it's implied by the role description that engineers will work on these aspects at some point in their career therein this company. • Years of experience: 3+ years • Education: Not explicitly stated; however, given the nature and level of responsibilities mentioned (working with hardware integrations, internal software for intake/fulfillment processes), a bachelor's degree or higher in computer science, engineering, information technology, or related field is likely required but not directly specified. • Certifications: Not explicitly stated; however, certifications such as CompTIA A+ could be beneficial due to the hardware integration aspect of the role and knowledge about internal software processes might benefit from a background understanding in systems administration which can often come with relevant IT certifications like Cisco CCNA or similar. • Must-haves: Direct impact on product development, ability to work across full stack (frontend/backend), experience working closely with users to identify bottlenecks and ship code that unlocks speed and scale are must-haves as explicitly stated in the job posting.
Responsibilities
• Work across the full stack—frontend, backend, and occasionally hardware. The problems are tangible and the feedback is fast: you might train the AI model that detects a check inside a document, then write the integration that extracts the data to deposit it, then watch it run in a real warehouse the same week. • Supporting 10,000+ businesses with a lean team means we focus on impact: Engineers talk to users, identify real-world bottlenecks, and ship code that unlocks speed and scale.
Benefits
• Supporting a lean team focused on impactful engineering. • Direct role in shaping core systems of the product. • Opportunity to work across frontend, backend, and hardware layers. • Fast feedback loop with tangible problems and solutions implemented quickly (e.g., training AI models within weeks).
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