Platform Engineer - Content Protection

Platform Engineer - Content Protection

About the Springer Nature Group

Springer Nature opens the doors to discovery for researchers, educators, clinicians, and other professionals. Every day, around the globe, our imprints, books, journals, platforms, and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities. As AI, machine intelligence and agentic technologies reshape how research is discovered and consumed, we have a responsibility to ensure knowledge remains both discoverable and protected.

About the role

The way academic research is communicated is changing rapidly. Increasingly, Springer Nature content is being accessed through search engines, discovery platforms, AI-powered services, machine agents and content aggregation ecosystems. This creates significant opportunities to extend the reach and impact of research, but also introduces new challenges around content extraction, automated access, platform stability and commercial value protection.

The Platform Engineer - Content Protection role sits within the Off-platform Discovery and Content Protection team and is responsible for turning analytical insight and content protection strategy into operational controls. Working closely with the Data Analyst, Product Manager, Managed Security Services, SEO teams, Product teams and Platform Engineering teams, this role owns the design, implementation and operation of traffic management and content protection controls.

The role is responsible for ensuring Springer Nature can maximise discoverability while protecting content, platform performance and future business models. You will continuously evolve controls and responses to address emerging forms of automated access, including AI-driven and agentic technologies, while ensuring legitimate users retain access to our platforms and content.

Responsibilities

Content Protection Execution & Operational Ownership

Build, operate and continuously improve WAF signals, policies and rules that detect and mitigate automated scraping, content extraction and abusive traffic.

Own the lifecycle of traffic protection controls including design, testing, deployment, tuning, validation and retirement.

Implement rate-limiting, bot-management and traffic-shaping strategies aligned to business objectives and platform requirements.

Ensure protection controls are effective without negatively impacting legitimate discoverability, accessibility or customer experience.

Turn analytical signals and intelligence into practical enforcement controls and measurable operational outcomes.

Incident Management & Response

Lead response activities relating to scraping, automated abuse, enumeration and traffic-related incidents.

Maintain operational playbooks and runbooks for detection, escalation, mitigation and recovery.

Implement controls using staged rollout approaches, balancing risk reduction with customer impact.

Monitor effectiveness of controls and continually improve protection capabilities.

Fastly Partnership & Vendor Management

Own the day-to-day technical relationship with Fastly MSS and associated content protection tooling.

Review, validate and operationalise Fastly recommendations and outputs.

Work with Fastly to maximise value from platform capabilities and identify future improvement opportunities.

Coordinate changes with stakeholders and communicate impacts, dependencies and implementation plans.

Cross-functional Collaboration & Future Capability Development

Partner closely with the Data Analyst to operationalise detection signals and validate outcomes.

Work with SEO teams to ensure legitimate crawlers and discovery services remain appropriately supported.

Support Product and Platform teams with traffic-aware architectural decisions.

Help define organisational policies relating to acceptable, non-desirable and malicious automated access.

Contribute to future approaches for managing AI agents, machine access and emerging content consumption models.

• What's Expected
• In 1–3 Months:

Build strong relationships with Managed Services vendor, Product, Platform Engineering, SEO and Analytics stakeholders.

Develop an understanding of existing WAF configurations, controls and operating processes.

Review recent incidents and identify immediate improvement opportunities.

Begin establishing operational playbooks and governance processes.

By 3–6 Months you will:

Establish repeatable workflows for traffic anomaly detection and response.

Create clear ownership and decision-making processes for content protection activities.

Reduce engineering involvement in reactive mitigation activities.

Deliver measurable improvements in response capability and operational readiness.

By 6–12 Months you will:

Operate a mature content protection capability integrated into platform operations.

Develop trusted partnerships with Fastly and internal stakeholders.

Improve protection against both high-volume and slow accumulation content extraction techniques.

Lay the foundations for managing AI-driven and agentic access patterns at scale.

Help Springer Nature balance discoverability, content protection and future commercial opportunities.

Essential Skills & Experience

Hands-on WAF engineering experience, ideally with Fastly Next-Gen WAF (Signal Sciences) or equivalent platforms.

Experience implementing bot management, rate limiting and traffic management controls.

Experience responding to scraping, DDoS, automated abuse or similar traffic-management incidents.

Strong understanding of HTTP, TLS, CDN and edge technologies.

Ability to balance security, operational and business considerations when designing controls.

Strong stakeholder management and communication skills.

Desirable

Experience with Fastly, Signal Sciences, edge compute or similar technologies.

Experience working alongside security operations or managed security services teams.

Experience with entitlement, identity or access-management systems.

Understanding of SEO, crawler behaviour and digital discoverability ecosystems.

Experience in academic publishing, research platforms or content-rich digital businesses.

Experience working with emerging AI, agentic or machine-access use cases.

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