Full Stack Developer

Summary

The Full Stack Developer will design, build, deploy, and maintain scalable software solutions that support the software needs of the Plant Sciences Team. The role combines python-based full stack engineering, data pipelining, and production of ml workflows to deliver reliable business and scientific applications. The developer will contribute to ERP and related module development, user-facing applications, and specialized solutions involving geospatial data, computer vision, and bioinformatics workflows.

Key Responsibilities

• Design, develop, test, and maintain full stack web applications using Python and modern front-end technologies.
• Provide ongoing software maintenance, troubleshooting, performance improvements, documentation, and production support for applications used by multiple teams.
• Develop and enhance ERP capabilities and other modular software components, including system integrations, data workflows, and user-facing features.
• Manage CI/CD pipelines in Microsoft Azure using Terraform, etc.
• Create intuitive, accessible, and responsive user interfaces that simplify complex workflows for technical and non-technical users.
• Deploy applications and services across development, test, and production environments, with appropriate logging, monitoring, security, and release practices.
• Write clean, modular, tested, and well-documented code, and participate in code reviews, architecture discussions, and technical planning.
• Work with stakeholders to prioritize enhancements, resolve defects, and balance new development with long-term system maintainability.

Typical Education

Bachelor’s degree in computer science or a closely related field with at least 3 years of relevant industry experience, or a master’s degree with 1–2 years of relevant industry experience.

Relevant Experience

• Strong Python development experience, including building full stack web applications and production of APIs or services.
• Experience with user interface development using modern web technologies and frameworks.
• Practical experience developing and deploying applications in Azure.
• Experience using Terraform or a comparable Infrastructure as Code approach for repeatable cloud deployments.
• Working knowledge of software engineering practices, including version control, automated testing, CI/CD, observability, and technical documentation.
• Ability to work across business, scientific, and technical teams and convert requirements into clear, supportable solutions.
• Experience with data science, bioinformatics workflows, scientific computing, or biological data systems.
• Experience with laboratory information management systems or other lab information systems.
• Experience with computer vision, geospatial analysis, or location-based data products.
• Professional or academic background in biology/agronomy, or a related scientific discipline.
• Experience supporting ERP systems, modular enterprise applications, or cross-system integrations.
• Experience operationalizing machine learning workflows through cloud platforms and practices.