Role Overview
We are seeking a Senior Full Stack Software Engineer to design and develop a modern publication management system from the ground up. This role will contribute across the full technology stack user interfaces, APIs, business logic, and data layers to deliver a scalable, intuitive, and maintainable platform supporting publication tracking, curation workflows, reporting, and integrations.
Key Responsibilities
Design and develop end-to-end features across frontend, backend, and data layers.
Build modern, responsive user interfaces for publication management and curation workflows.
Develop and maintain backend services, APIs, and business logic.
Collaborate with architects to implement modern architectural patterns and design standards.
Translate business and user requirements into usable technical solutions.
Implement data models and persistence for complex bibliographic and metadata-driven systems.
Integrate with internal and external systems
Write clean, testable, and well-documented code.
Participate in code reviews and contribute to engineering best practices.
Troubleshoot, optimize, and improve application performance and usability.
Required Skills & Experience
Proven experience as a Senior Full Stack Software Engineer on enterprise-scale applications.
Strong proficiency in:
Frontend: Modern JavaScript frameworks (e.g., React, Angular, or Vue)
Backend: Java, Python, Node.js, or equivalent
Experience building and consuming RESTful APIs.
Solid understanding of modern software development practices, including:
Modular or microservices-based architectures
API-first design
Agile or iterative development
Experience with relational and/or NoSQL databases and data modeling.
Familiarity with cloud-native or hybrid deployment environments.
Strong problem-solving skills and attention to detail.
Excellent communication and collaboration skills.
Preferred Qualifications
Experience with greenfield development and phased delivery models.
Familiarity with publication management systems, research information systems.
Knowledge of scholarly metadata standards such as DOI, ORCID, MeSH, PubMed, or similar.
Experience building dashboards, reports, or data visualization features.
Background in research, healthcare, academic, or life sciences environments.
Nice-to-Have
Exposure to AI/ML-assisted features, such as metadata enrichment or intelligent classification.
Experience with CI/CD pipelines, containerization, and DevOps tooling.
Understanding of security, accessibility, and data governance best practices.
What Success Looks Like
Delivery of intuitive, high-quality user interfaces and robust backend services.
Well-architected, maintainable code supporting long-term scalability.
Strong collaboration with architects, analysts, and stakeholders.
Contributions that measurably improve usability, efficiency, and system reliability.
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