Springer Nature

Principal Developer

London Berlin
AI Kotlin React GCP LLM
Description

Principle Developer - Nature Research Assistant

Location: London, Berlin, Lisbon

Time Type: Full time

Job Description

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 knowledge remains discoverable, verifiable, and usable for generations to come. 

 

About the Role 

Springer Nature is seeking a visionary and execution‑focused Principal Developer with strong leadership capability to guide the technical direction of the Nature Research Assistant—an emerging AI‑driven product designed for the academic research community. 

This role requires someone who can bridge fast-paced AI innovation with enterprise-grade engineering, reduce bottlenecks, accelerate decision‑making, and maintain delivery velocity. You will work closely across SND, the central AI/ML group (SNAIL), DevOps, Product, and our external startup partners. 

With the product currently in closed 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 be required. 

 

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: 

  • Lead through influence, not just authority, and help teams make timely, well‑informed decisions 

  • Bring clarity when stakeholders or teams are misaligned 

  • Can balance best practices with speed—pushing for solutions that are fit for purpose, not over‑engineered 

  • Have strong awareness of modern AI/LLM technologies, including reliability, evaluation, safety, and latency constraints 

  • Value collective ownership, mentoring, and raising the bar for engineering excellence 

  • Are comfortable working across time zones and organisational silos 

  • Enjoy pairing, Test‑Driven Development, trunk‑based development, and continuous delivery 

  • Embrace failure as a learning opportunity 

  • Communicate clearly with both technical and non‑technical collaborators 

 

What’s Expected 

In your first 3 months 

  • Develop a deep understanding of the NRA technology stack—a Kotlin/http4k backend and React/Remix frontend 

  • Learn our deployment and infrastructure workflows on Google Cloud Platform (GCP) 

  • Contribute to feature development within the product team 

  • Understand the roles, expectations, and constraints of SNAIL (central AI/ML), DevOps, Product Management, and external partners 

  • Help evolve the team’s agile processes and ceremonies 

  • Understand the team and product context within the academic publishing industry 

  • Begin identifying key bottlenecks and opportunities to improve velocity 

 

By 3–6 months 

  • Lead the technology direction for NRA, selecting appropriate solutions to solve the problems at hand 

  • Mentor team members across locations and support cross‑team collaboration 

  • Translate high‑level product objectives into actionable engineering work 

  • Advocate for defining and implementing strong non‑functional requirements 

  • Guide architectural decisions and clearly articulate trade‑offs 

  • Strengthen AI integration through collaboration with the ML/AI team, focusing on evaluation, reliability, and observability 

  • Help reduce cross‑team friction, enabling faster and clearer decision cycles 

 

By 6–12 months 

  • Support onboarding of new team members and contribute to building a cohesive, high‑performing team 

  • Provide actionable, constructive feedback to engineers and stakeholders 

  • Diagnose and resolve issues in live applications, contributing to blameless post‑mortems 

  • Deepen understanding of user needs and ensure technical decisions reflect the researcher experience 

  • Drive improvements in stability, performance, and iteration speed 

  • Demonstrate measurable improvements in delivery flow, architectural clarity, and collaboration effectiveness 

 

Springer Nature Skills Associated With This 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 

 #LI-AR1

Springer Nature
Springer Nature

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