Lead Architect, Application & Product- AI

Position Overview

Basic Function

As Lead Application & Product Architect, you will play a central technical role in shaping our new cloud, AI, and agentic products and the broader platform. You will own architecture direction and technical guardrails across application, data, integration, cloud, and AI capabilities, ensuring that high delivery velocity, AI-native development, and technical excellence are sustainably combined. You will establish pragmatic, production-grade architecture patterns that engineering teams can directly execute and evolve through Spec-Driven Development and Architecture-as-Code practices. You will also ensure architecture decisions meet Wolters Kluwer requirements for security, data protection, risk, compliance, and governance.

Essential Duties & ResponsibilitiesEssential Duties and responsibilities

• Own the architecture of new cloud and AI products and the overarching platform, ensuring a consistent cloud-first, API-first, and agentic-first approach.

• Define architecture standards and technical guardrails, and make architecture decisions with scalability, maintainability, security, quality, and technical risk in mind.

• Analyze existing products, platforms, and architectures and develop pragmatic evolution and migration paths that account for existing investments and technical dependencies.

• Serve as a technical thought partner to Product and Engineering roles, conduct architecture, design, and security reviews, and consistently advocate for sound technical decisions when stakeholder interests differ.

• Ensure solutions meet Wolters Kluwer internal requirements for architecture, security, data protection, risk, compliance, and governance, working closely with the relevant control and governance functions.

• Define architecture patterns for production-grade AI and agentic capabilities, including context engineering, evaluation, observability, performance, security, governance, traceability, and cost optimization.

• Define integration patterns across applications, data, APIs, AI models, and agents, including agent-to-agent and Model Context Protocol (MCP)-based interactions where appropriate.

• Establish architectural patterns for AI evaluation and validation, including quality, reliability, performance, security, and regression evaluation throughout the product lifecycle.

• Ensure application and data architectures support AI-enabled products through scalable data access, data quality, lineage, governance, and appropriate batch, real-time, and event-driven patterns.

• Create actionable, version-controlled architecture artifacts using Architecture-as-Code practices, including reference architectures, specifications, architecture decision records (ADRs), integration contracts, and reference implementations that engineering teams can directly use and evolve through delivery.

Job Qualifications

Education:

Bachelor’s degree in computer science, Software Engineering, Information Systems, or a related field, or equivalent practical experience. Master’s degree in a relevant technical or business discipline is preferred.

Required Experience / Skills:

• 10+ years of software engineering experience, including significant application or product architecture responsibility for complex commercial software.

• Hands-on experience architecting AI/ML, generative AI, or agentic capabilities within customer-facing production software is required.

• Practical experience with Agentic Product Development Lifecycle and Spec-Driven Development, including architecture specifications, evaluation strategies, and traceability.

• Experience designing secure AI-enabled systems, including data protection, identity, access controls, threat modeling, and AI-specific security risks.

• Strong expertise in cloud-native architectures, APIs, microservices, distributed systems, and integration architectures.

• Experience with modern technology stacks, as well as CI/CD, DevSecOps, and automated quality gates.

• Experience quickly understanding existing enterprise and legacy architectures and evolving them incrementally.

• Knowledge of Enterprise Architecture, Security, Risk, Compliance, and Architecture Governance, with the ability to incorporate these requirements into technical solutions early in the lifecycle.

Knowledge, Skills, and Abilities:

• Strong systems-thinking skills with the ability to reason across application, data, integration, cloud, AI and agentic, security, and operational architecture and translate complex systems into clear architectural boundaries and patterns.

• Exceptional architectural judgment with the ability to evaluate trade-offs across scalability, resiliency, security, performance, cost, maintainability, delivery speed, and technical debt.

• Strong understanding of production AI and agentic architecture, including context engineering, evaluation, orchestration, observability, traceability, model and agent integration, security, and token and cost optimization.

• Strong understanding of modern data architecture, including data modeling, lineage, data quality, governance, scalable access patterns, and batch, real-time, and event-driven integration.

• Ability to apply Architecture-as-Code and Spec-Driven Development practices by creating version-controlled, traceable architecture artifacts that evolve with implementation rather than becoming static documentation.

• Strong understanding of production architecture, including observability, telemetry, reliability, resiliency, performance, deployment architecture, incident diagnostics, and operational effectiveness.

• Ability to lead through technical influence, establish architectural direction and guardrails, resolve competing technical viewpoints, and drive alignment across Product, Engineering, Security, Data, and platform teams without relying on direct authority.

• Ability to simplify complex technology landscapes, identify reusable capabilities and patterns, reduce unnecessary architectural variation, and avoid over-engineering.

• Strong communication and influencing skills, with the ability to explain complex technical concepts clearly to technical and nontechnical stakeholders.

• Ability to facilitate fact-based discussions on controversial topics and sustain sound architecture decisions under significant delivery pressure.

• Ability to balance high delivery velocity, AI-native development, technical excellence, and enterprise governance requirements.

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Compensation:

Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.

Additional Information:

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.