Lead Product Architect

Wolters Kluwer•Coppell, TX

4d•$107,500 - $188,400

About The Position

The Lead Product Architect defines and drives technical vision, architecture strategy, and engineering direction across a portfolio of products and platforms. The role provides architectural leadership for product development, modernization, AI-enabled solutions, platform engineering, and enterprise integration. It partners with Product Management, Engineering Leadership, UX, Security, DevOps, Data, and Business stakeholders to deliver scalable, secure, resilient, and future-ready solutions, while guiding teams in AI-first engineering practices and modern architecture patterns. The architect establishes end-to-end product architectures, technical standards, roadmaps, and governance, and provides guidance on cloud-native engineering, distributed systems, enterprise integration, and modernization. The role also designs and governs AI-enabled products and reusable AI capabilities, and champions Spec-Driven Development and Agentic SDLC practices. It supports engineering teams through architecture reviews, design coaching, implementation guidance, proof-of-concepts, and adoption of AI-assisted development tools. The position calls for extensive software architecture and engineering expertise, Azure and cloud platform knowledge, modern AI application design, and demonstrated technical leadership across multiple teams and product areas. A bachelor's or master's degree and extensive experience are preferred qualifications rather than explicitly stated mandatory requirements.

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.
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, responsible AI design, Spec-Driven Development, Agentic SDLC, developer productivity platforms, AI coding assistants, AI-powered search, recommendations, workflow automation, and 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.
Capability 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+ years of software engineering and architecture experience.
5+ 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.
Provide oversight for 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 standards for AI safety, grounding, observability, evaluation, prompt management, and responsible AI practices.
Guide teams building AI-native applications that balance business value, reliability, security, and compliance.
Evaluate emerging AI technologies and identify opportunities to enhance products, customer experiences, and engineering productivity.
Support architecture and governance for enterprise AI platforms and reusable AI capabilities.
Champion Spec-Driven Development across engineering teams.
Define architecture patterns, standards, and reusable templates for AI-assisted software development.
Partner with engineering teams to create specifications consumable by AI coding agents and automation platforms.
Enable Agentic SDLC through architectural 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 align with architectural principles, quality standards, and security requirements.
Lead modernization initiatives involving legacy application transformation, cloud migration, platform modernization, API strategies, and microservices adoption.
Drive architectural improvements that reduce technical debt and improve engineering agility.
Design and oversee implementation of cloud-native architectures and distributed systems.
Collaborate with engineering teams to optimize performance, observability, reliability, and operational maturity.
Guide teams on APIs, event-driven systems, integration platforms, and platform engineering capabilities.
Promote engineering excellence through architecture reviews, design coaching, and implementation guidance.
Lead proof-of-concepts and architecture spikes to validate emerging technologies and solution approaches.
Drive adoption of AI-assisted development capabilities, including GitHub Copilot, coding agents, automated testing, code review assistants, and developer productivity platforms.
Establish best practices for AI-assisted engineering and AI-enabled architecture design.
Collaborate with Product and Engineering leaders to identify automation and engineering acceleration opportunities.
Create reusable architectural assets, design patterns, reference implementations, and engineering frameworks.
Partner with Product Management, Engineering Managers, Architects, Security, UX, QA, DevOps, and Data teams.
Facilitate architecture reviews, technical planning sessions, and strategic technology discussions.
Communicate architectural decisions and technical trade-offs to technical and business audiences.
Influence technology direction through data-driven recommendations and architectural leadership.
Advise engineering leadership on architecture strategy, technology investments, modernization priorities, and AI adoption.