Forward Deployed Engineer

About the Role

Wolters Kluwer Health has a strong foundation in trusted clinical decision support. We are extending that foundation into outcome-focused solutions that connect clinical content, data, AI, and workflow to help customers improve clinical, operational, financial, and experience outcomes. The Forward Deployed Engineer is a product-minded, hands-on engineer who works with strategic customers and WK teams to discover high-value problems, build working solutions, validate impact, and turn repeatable patterns into scalable WK Health capabilities.

The role reports into Technology and partners closely with Product. This is not a professional services, implementation delivery, or sales engineering role. It is a product-embedded engineering role that learns from real customer environments, accelerates adoption of WK Health platforms, and shapes reusable product direction across the Health division, including AI-enabled capabilities building on the momentum of our Expert AI propositions.

The FDE owns the path from customer problem to technical proof, measured outcome, and product feedback. They build fast, practical solutions while protecting safety, security, quality, and long-term maintainability. No direct reports are expected initially; the role may lead cross-functional virtual squads or technical work streams.

Essential Duties and Responsibilities:

Discover and Frame Outcomes. Work with customer executives, clinical leaders, informaticists, pharmacists, IT/data teams, and end users to understand workflows, constraints, decision points, and adoption barriers. Translate ambiguous needs into outcome hypotheses, use cases, success metrics, acceptance criteria, prototypes, and implementation options anchored in measurable customer value. Build, Integrate, and Validate Design, code, integrate, test, and deploy prototypes and product extensions using WK Health assets, APIs, data, AI capabilities, and platform services.

Apply healthcare integration patterns where appropriate, including HL7 FHIR, SMART on FHIR, CDS Hooks, secure APIs, and cloud-native approaches. Use modern engineering practices, including Spec Driven Development, automated testing, observability, secure SDLC, and AI-assisted or agentic development with human accountability. Make Field Learning Reusable Design with reuse as the default; convert field-built patterns into APIs, connectors, reference architectures, templates, evaluation harnesses, playbooks, and product backlog input.

Work with Product and Engineering to determine what should become a platform capability, packaged solution, roadmap priority, or retired one-off pattern. Navigate Responsibly Build AI-enabled workflows grounded in trusted content, clear user intent, human oversight, auditability, and post-deployment monitoring. Partner with clinical, editorial, security, privacy, legal, and compliance teams to align solutions with WK responsible AI principles, healthcare safety, and data governance expectations.

Create alignment across WK and customer teams with clarity, humility, curiosity, and judgment; communicate tradeoffs and push for impact without creating unsupported customization or unmanaged risk.

• Bachelor’s degree in computer science, Software Engineering, Biomedical Informatics, Data Science, Health Informatics, Engineering, or equivalent practical experience.
• Advanced degree preferred but not required.
• 7+ years in software engineering, customer-facing engineering, solution architecture, technical product management, or related product technology roles.
• Production-quality software experience in enterprise &/or regulated environments.
• Healthcare technology experience across clinical workflows, EHR/payer/pharmacy systems, healthcare data platforms, or digital health. (HL7 FHIR, SMART on FHIR, CDS Hooks, RxNorm, SNOMED CT, LOINC, ICD-10, CPT, NDC, Integration with Epic, Oracle Health/Cerner, MEDITECH, Athenahealth, payer platforms)
• Modern software delivery with AI/GenAI, LLMs, RAG, agentic workflows, AI evaluation, prompt/retrieval testing, or responsible AI governance.
• Ability to turn customer or stakeholder problems into…