Lead Product Architect

Role Summary

The Lead Product Architect is responsible for defining and driving the technical vision, architecture strategy, and engineering direction for a portfolio of products and platforms. This role provides architectural leadership across product development, modernization initiatives, AI-enabled solutions, platform engineering, and enterprise integration efforts.

The ideal candidate combines deep expertise in software architecture, cloud-native engineering, distributed systems, and AI-powered application design with a strong understanding of modern software delivery practices, including Spec-Driven Development (SDD), Agentic SDLC, AI-assisted development, and developer productivity platforms.

This individual will partner closely with Product Management, Engineering Leadership, UX, Security, DevOps, Data, and Business stakeholders to deliver scalable, secure, resilient, and future-ready solutions. In addition to shaping architecture, the role will actively guide engineering teams in adopting AI-first engineering practices and modern architecture patterns that accelerate delivery while maintaining quality, security, and governance standards.

Key Responsibilities

Product & Solution Architecture Leadership

• •Define and maintain end-to-end product architecture aligned with business strategy, product roadmaps, and enterprise standards.
• •Lead architecture and design reviews across multiple product initiatives and engineering teams.
• •Develop architectural blueprints, solution designs, reference architectures, and technical standards.
• •Ensure systems meet requirements for scalability, reliability, performance, security, maintainability, and operational excellence.
• •Provide oversight for architectural governance and critical technical decisions.
• •Evaluate technology options and establish long-term technical roadmaps.

AI Architecture & AI-Powered Product Engineering

• •Design and govern architectures for AI-enabled products, intelligent workflows, agentic systems, conversational experiences, and retrieval-augmented generation (RAG) solutions.
• •Define patterns for integrating Large Language Models (LLMs), AI agents, semantic search, vector databases, orchestration frameworks, and AI-powered business workflows.
• •Establish architectural standards for AI safety, grounding, observability, evaluation, prompt management, and responsible AI practices.
• •Guide teams in 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.

Spec-Driven Development & Agentic SDLC

• •Champion Spec-Driven Development methodologies across engineering teams.
• •Define architecture patterns, standards, and reusable templates that enable AI-assisted software development.
• •Partner with engineering teams to create specifications that can be consumed by AI coding agents and automation platforms.
• •Enable Agentic SDLC practices 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.

Technical Leadership & Modernization

• •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 architecture patterns involving APIs, event-driven systems, integration platforms, and platform engineering capabilities.
• •Promote engineering excellence through architecture reviews, design coaching, and implementation guidance.

Innovation, Prototyping & AI-Assisted Development

• •Lead proof-of-concepts and architecture spikes to validate emerging technologies and innovative 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 opportunities for automation and engineering acceleration.
• •Create reusable architectural assets, design patterns, reference implementations, and engineering frameworks.

Cross-Functional Leadership & Collaboration

• •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 both technical and business audiences.
• •Influence technology direction through data-driven recommendations and architectural leadership.
• •Serve as a trusted advisor to engineering leadership on architecture strategy, technology investments, modernization priorities, and AI adoption.

Required Skills & Expertise

Architecture & Engineering

• •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.

Cloud & Platform Technologies

• •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.

AI & Modern Software Engineering

• •AI-assisted software development.
• •Generative AI application architecture.
• •Agentic systems and AI orchestration frameworks.
• •Retrieval-Augmented Generation (RAG).
• •Prompt engineering and evaluation frameworks.
• •AI safety, governance, and responsible AI design.
• •Spec-Driven Development.
• •Agentic SDLC.
• •Developer productivity platforms and AI coding assistants.
• •AI-powered search, recommendations, workflow automation, and intelligent document processing.

Leadership & Influence

• •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.

Preferred Qualifications

• •Bachelor's or Master’s Degree in Computer Science, Software Engineering, Information Systems, AI or 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, 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.

Preferred Certifications

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