Note: The job is a remote job and is open to candidates in USA. Pivotly builds software that eliminates manual data entry from mission-critical business workflows through two products. As a Senior Software Engineer at Pivotly, you will design, build, and maintain the backend services that power their AI-automated, human-verified workflow platform, collaborating closely with product, operations, and AI/ML teams.

Responsibilities

• Design, build, and maintain production-grade backend services and APIs that power Pivotly’s core automation workflows
• Own features end to end: refine requirements, design system components, write clean and testable code, and monitor performance in production
• Contribute to architecture discussions and help drive continuous improvement of engineering practices, tooling, and infrastructure
• Participate in code reviews with a focus on maintainability, reliability, and security
• Collaborate cross-functionally with product, operations, and AI/ML teams to deliver high-impact solutions
• Communicate clearly and proactively with technical and non-technical stakeholders across time zones
• Produce thorough documentation to support team alignment and long-term maintainability

Skills

• 5–8 years of professional software engineering experience, with a strong track record of delivering production-grade systems
• Strong computer science foundations: data structures, algorithms, and software design principles
• Advanced back-end development experience, including RESTful APIs, microservices, and database design
• Deep proficiency in object-oriented programming and best practices for clean, maintainable, testable code
• Hands-on experience designing and operating cloud-based architectures (AWS, GCP, or Azure), including monitoring, logging, and performance tuning
• Proficiency with modern development workflows: Git, CI/CD pipelines, and automated testing
• Strong async communication skills and the ability to work autonomously in a fully remote environment
• Bachelor's degree in Computer Science, Engineering, or a related field — or equivalent practical experience
• Prior experience with data-intensive systems, workflow automation, or AI/ML-driven products is a strong plus

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