Lead Product Architect

Wolters Kluwer•Coppell, TX

2d•$107,500 - $188,400

About The Position

The Lead Product Architect defines and drives the technical vision, architecture strategy, and engineering direction for a portfolio of products and platforms. The role provides architectural leadership across product development, modernization, AI-enabled solutions, platform engineering, and enterprise integration. It combines expertise in software architecture, cloud-native engineering, distributed systems, and AI-powered application design with modern delivery practices such as Spec-Driven Development (SDD), Agentic SDLC, AI-assisted development, and developer productivity platforms. The architect partners with Product Management, Engineering Leadership, UX, Security, DevOps, Data, and business stakeholders to deliver scalable, secure, resilient, and future-ready solutions. The role also guides engineering teams in adopting AI-first practices and modern architecture patterns while maintaining quality, security, and governance standards. The position includes defining product and solution architecture; designing and governing AI-powered products and enterprise AI capabilities; advancing SDD and Agentic SDLC practices; leading modernization and cloud-native initiatives; prototyping emerging technologies; promoting AI-assisted development; and advising engineering leadership on architecture strategy, technology investments, and AI adoption. The preferred qualifications include a technical bachelor's or master's degree, extensive software engineering and architecture experience, and relevant architecture, cloud, AI, or Kubernetes certifications. Compensation is listed as $107,500–$188,400 USD, and the role is eligible for a bonus. The employer notes that applicants may be required to appear onsite at a Wolters Kluwer office during recruitment.

Requirements

Extensive experience designing enterprise-scale software products and platforms.
Strong expertise in application architecture, solution architecture, and distributed systems design.
Deep understanding of cloud-native architectures and modern engineering practices.
Experience designing scalable APIs, event-driven systems, microservices, and platform architectures.
Strong knowledge of security, resiliency, observability, performance, and operational architecture.
Experience with enterprise integration patterns and complex system landscapes.
Expertise with Azure environments and experience architecting cloud-native applications and platform services.
Strong understanding of DevSecOps, CI/CD, Infrastructure as Code, and Platform Engineering.
Experience with container technologies, Kubernetes, service meshes, and enterprise integration platforms.
Knowledge or experience in AI-assisted software development, generative AI application architecture, agentic systems, AI orchestration frameworks, RAG, prompt engineering and evaluation frameworks, AI safety and governance, Spec-Driven Development, Agentic SDLC, developer productivity platforms, AI coding assistants, and AI-powered search, recommendations, workflow automation, or intelligent document processing.
Strong architectural leadership and technical mentoring experience.
Ability to influence engineering teams and stakeholders without direct authority.
Excellent communication and stakeholder management skills.
Ability to lead architecture initiatives across multiple teams and product areas.
Strong analytical thinking and complex problem-solving abilities.

Nice To Haves

Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, AI, or a related technical field.
12 or more years of software engineering and architecture experience.
5 or more years in Solution Architect, Product Architect, or Principal Architect roles.
Experience with .NET, Angular, MS SQL, or Oracle.
Experience with AI/ML-enabled products, enterprise AI platforms, or LLM-powered solutions.
Experience with application modernization and legacy platform transformations.
Experience supporting enterprise SaaS and cloud-based software products.
Microsoft Azure Solutions Architect Expert certification.
TOGAF certification.
ArchiMate certification.
Kubernetes certification (CKA/CKAD).
Azure AI Engineer Associate certification.
AI Architecture, Prompt Engineering, or Generative AI certifications.

Responsibilities

Define and maintain end-to-end product architecture aligned with business strategy, product roadmaps, and enterprise standards.
Lead architecture and design reviews across product initiatives and engineering teams; develop architectural blueprints, solution designs, reference architectures, and technical standards.
Ensure systems meet scalability, reliability, performance, security, maintainability, and operational excellence requirements; oversee architectural governance and critical technical decisions.
Evaluate technology options and establish long-term technical roadmaps.
Design and govern architectures for AI-enabled products, intelligent workflows, agentic systems, conversational experiences, and RAG solutions.
Define patterns for integrating LLMs, AI agents, semantic search, vector databases, orchestration frameworks, and AI-powered business workflows.
Establish AI architecture standards for safety, grounding, observability, evaluation, prompt management, and responsible AI; guide teams building AI-native applications and support enterprise AI platforms and reusable capabilities.
Champion Spec-Driven Development and define architecture patterns, standards, and templates for AI-assisted software development.
Partner with engineering teams to create specifications for AI coding agents and automation platforms; enable Agentic SDLC through guardrails, AI-enabled workflows, and development automation.
Define standards for requirements decomposition, architecture artifacts, code generation, testing automation, and deployment workflows; ensure AI-generated outputs meet architecture, quality, and security standards.
Lead legacy application transformation, cloud migration, platform modernization, API strategies, and microservices adoption; reduce technical debt and improve engineering agility.
Design and oversee cloud-native architectures and distributed systems; collaborate with teams to improve performance, observability, reliability, and operational maturity.
Guide teams on APIs, event-driven systems, integration platforms, and platform engineering; provide architecture reviews, design coaching, and implementation guidance.
Lead proof-of-concepts and architecture spikes to validate emerging technologies and innovative approaches.
Drive adoption of AI-assisted development tools and practices, including GitHub Copilot, coding agents, automated testing, code review assistants, and developer productivity platforms.
Create reusable architectural assets, design patterns, reference implementations, and engineering frameworks; collaborate with Product and Engineering leaders on automation and engineering acceleration.
Partner with Product Management, Engineering Managers, Architects, Security, UX, QA, DevOps, and Data teams; facilitate architecture reviews, technical planning, and strategic technology discussions.
Communicate architecture decisions and trade-offs to technical and business audiences; influence technology direction with data-driven recommendations.
Advise engineering leadership on architecture strategy, technology investments, modernization priorities, and AI adoption.