Principle Developer, Nature Research Assistant
About the Springer Nature Group
Springer Nature opens the doors to discovery for researchers, educators, clinicians, and professionals around the globe. For over 175 years, our imprints, books, journals, platforms, and technology solutions have supported communities in advancing knowledge and improving outcomes. Today, we continue to invest in innovation to ensure that foundational knowledgeremainsdiscoverable, verifiable, and usable for generations to come.
About the Role
Springer Nature is seeking a visionary and execution‑focusedPrincipal Developerwith strong leadership capability to guide the technical direction of theNature Research Assistant—an emerging AI‑driven product designed for the academic research community.
This role requires someone who canbridge fast-paced AI innovation with enterprise-grade engineering, reduce bottlenecks, accelerate decision‑making, andmaintaindelivery velocity. You will work closely across SND, the central AI/ML group (SNAIL), DevOps, Product, and our external startup partners.
With the product currently inclosed beta, you will join at a pivotal point—helping shape the architecture, strengthen AI integration, and scale the platform for broader rollout.
You will work within a dynamic, collaborative, cross‑functional environment that is passionate about advancing science through technology.
The role can be based in any of our main European Digital locations (London, Lisbon, Berlin) and involves remote collaboration with colleagues in our global offices including Pune (India), Dordrecht and Groningen (The Netherlands), London (UK), and Berlin (Germany). Some travel may berequired.
About You
You are a technology leader who excels in enabling teams, navigating ambiguity, and driving pragmatic delivery. You combine deep engineering experience with the ability to influence across organisational boundaries.
You will enjoy this role if you:
1. Lead through influence, not just authority, and help teams maketimely, well‑informed decisions
2. Bring clarity when stakeholders or teams are misaligned
3. Can balance best practices with speed—pushing for solutions that arefit for purpose, not over‑engineered
4. Have strong awareness of modernAI/LLM technologies, including reliability, evaluation, safety, and latency constraints
5. Value collective ownership, mentoring, and raising the bar for engineering excellence
6. Are comfortable working across time zones and organisational silos
7. Enjoy pairing, Test‑Driven Development, trunk‑based development, and continuous delivery
8. Embrace failure as a learning opportunity
9. Communicate clearly with both technical and non‑technical collaborators
What’s Expected
In your first 3 months
10. Develop a deep understanding of the NRA technology stack—aKotlin/http4kbackend andReact/Remixfrontend
11. Learn our deployment and infrastructure workflows onGoogle Cloud Platform (GCP)
12. Contribute to feature development within the product team
13. Understand the roles, expectations, and constraints of SNAIL (central AI/ML), DevOps, Product Management, and external partners
14. Help evolve the team’s agile processes and ceremonies
15. Understand the team and product context within the academic publishing industry
16. Beginidentifyingkey bottlenecks and opportunities to improve velocity
By 3–6 months
17. Lead the technology direction for NRA, selectingappropriate solutionsto solve the problems at hand
18. Mentor team members across locations and support cross‑team collaboration
19. Translate high‑level productobjectivesinto actionable engineering work
20. Advocate for defining and implementing strong non‑functional requirements
21. Guide architectural decisions and clearly articulate trade‑offs
22. Strengthen AI integration through collaboration with the ML/AI team, focusing on evaluation, reliability, and observability
23. Help reduce cross‑team friction, enabling faster and clearer decision cycles
By 6–12 months
24. Support onboarding of new team members and contribute to building a cohesive, high‑performing team
25. Provide actionable, constructive feedback to engineers and stakeholders
26. Diagnose and resolve issues in live applications, contributing to blameless post‑mortems
27. Deepen understanding of user needs and ensure technical decisions reflect the researcher experience
28. Drive improvements in stability, performance, and iteration speed
29. Demonstrate measurable improvements in delivery flow, architectural clarity, and collaboration effectiveness
Springer Nature Skills AssociatedWithThis Role
SN‑Action‑Oriented · SN‑Tech Savvy · SN‑Cultivates Innovation ·
SN‑Data Security & Governance · SN‑Quality Management ·
SN‑Process & Systems Design · SN‑Product Development & Delivery ·
SN‑Software Engineering & Systems Integration · SN‑Collaboration · SN‑Drives Results
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