Fullstack Software Engineer

About the role

We are looking for a Fullstack Software Engineer to own and evolve our web platform, desktop scanner client, and AI‑powered processing pipelines. You will work closely with product and operations teams to turn real‑world document processing needs into reliable software solutions.

Key responsibilities

• Build and maintain the web platform, including backend APIs, background job processing, database models, and a browser‑based template editor for OMR zones.
• Develop and support a desktop application that interfaces with document scanners and the cloud backend.
• Integrate scanner hardware using industry‑standard drivers, SDKs and vendor APIs to ensure accurate capture, validation and upload.
• Incorporate AI services such as LLMs for template generation, computer‑vision layout detection, and OCR/ICR for handwritten and printed responses.
• Design high‑throughput processing pipelines, managing job queues, concurrency, rate‑limited AI calls and cloud object storage.
• Collaborate with Product Managers and Operations to translate workflow requirements into robust software.
• Uphold engineering quality through test‑driven development, strong typing, clean architecture, CI/CD pipelines and thorough documentation.

Required profile

• Deep understanding of core software engineering principles; ability to design systems under constraints and articulate trade‑offs.
• Strong grasp of concurrency models (threads, event loops, async/await) and experience debugging across system boundaries.
• Proactive testing mindset – writing tests before code to avoid regressions.
• Comfort working with hardware or device integration, even without being an embedded specialist.

Required skills

• Full‑stack web development (frontend & backend APIs) and relational database experience.
• Desktop application development (native or Electron‑based).
• Hardware integration using SDKs, USB/Serial interfaces and vendor APIs.
• AI/ML API integration with handling of rate limits, retries and output evaluation.
• Cloud infrastructure knowledge – containers, managed services, object storage and job queues.
• Software hygiene practices: version control (Git), automated testing (TDD), code reviews.