Overview
In this role, you will help build document intelligence capabilities to understand scientific content at scale. You will work on cloud-native services that transform manuscripts into structured data, enabling smarter submission and editorial experiences. You collaborate with cross-functional teams to drive architecture, delivery, and observability, aligning with a culture of innovation. This is a hands-on role at the intersection of software, data engineering, and AI/LLM, with impact on the Submission portfolio. You will contribute to scalable, reliable systems that power AI-driven features across publishing workflows.
Pay / Benefits
- Comprehensive Pension Plan
- Generous vacation entitlement and sabbatical option
- Maternity, Paternity, Adoption and Family Care leave
- Personal Choice budget
- Internal communities and networks
- Employee discounts
Responsibilities
- Design, develop, and deploy cloud-hosted distributed applications for the next-generation product
- Collaborate with business stakeholders to gather requirements in a fast-moving environment
- Influence architecture to ensure stability and performance
- Improve delivery processes through iterative enhancements
- Partner with cross-functional Agile and DevOps teams
- Own services across their lifecycle including architecture, deployment, observability, and ongoing improvement
Key requirements
- Proficiency in Python and Java, with Spring / Spring Boot, SQL; willingness to learn other tech
- Experience with distributed/event-driven architectures using Kafka and AWS
- Experience with build tools, Git, and CI (GitHub Actions / Jenkins)
- Team-oriented with ability to mentor others and share knowledge
- Experience with monitoring/logging tools (New Relic, OpenSearch / Kibana, Coralogix)
- Familiarity with IDEs (IntelliJ / VSCode) and refactoring tools
- Exposure to TDD and mocking libraries (Jest, Mockito)
- Familiarity with Jira and Confluence; understanding of data-processing workflows and scalable backends
- Experience with Agile practices (Scrum, Kanban) and cloud-oriented design (Docker, Kubernetes)
- Awareness of AI coding tools (Copilot, Claude, Codex) and interest in AI-based solutions
- Collaborative mindset
- Mentorship and knowledge sharing
- Willingness to learn and adapt
- Python
- Java
- Spring / Spring Boot
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