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Guidewire QE Solution Architect – Insurance Leader

Job in Princeton, Mercer County, New Jersey, 08543, USA
Listing for: Zensar Technologies
Full Time position
Listed on 2026-02-10
Job specializations:
  • IT/Tech
    Cloud Computing, Data Analyst
Job Description & How to Apply Below

Overview

Guidewire QE Solution Architect – Insurance Leader

We are seeking a QE Architect – Insurance to lead Quality Engineering initiatives for Insurance clients, with a strong focus on Guidewire testing and domain-specific solutions.

Role-Overview

Role-Overview:

Responsibilities
  • Design and implement automation frameworks for Insurance platforms, including Guidewire (Policy Center, Billing Center, Claim Center).
  • Drive integration, regression, and data migration testing for insurance systems.
  • Provide consulting on underwriting, claims, and policy lifecycle processes.
  • Participate in client consulting engagements and provide high-impact recommendations for quality transformation.
  • Prepare solution approaches, proposals, and technical statements of work (SoW) tailored to client needs.
  • Design and architect full-stack automation frameworks covering Web, Mobile, API, Digital, and Database testing.
  • Drive Test Data Management (TDM) strategies to ensure robust and scalable test environments.
  • Perform technical assessments, identify gaps, and recommend strategic improvements to client quality engineering practices.
  • Champion adoption of AI/ML-based quality engineering approaches, intelligent test design, predictive analytics, and self-healing automation.
  • Participate in client consulting engagements and provide high-impact recommendations for quality transformation.
  • Prepare solution approaches, proposals, and technical statements of work (SoW) tailored to client needs.
  • Support new business pursuits, RFPs, RFIs, and proactive proposals with strong solution leadership.
  • Identify, nurture, and convert potential opportunities into revenue-generating engagements.
  • Collaborate with sales and account teams to position Quality Engineering as a business differentiator in client conversations.
  • Define and track metrics that link automation and AI-led quality solutions directly to client ROI and revenue outcomes.
  • Mentor, coach, and grow high-performing engineering teams across the region (US).
  • Foster a culture of innovation, continuous improvement, and cross-collaboration.

Partner with global practice leaders to ensure alignment and knowledge sharing across geographies.

Required Qualifications
  • 15+ years of experience in Software Testing, Test Automation, and Quality Engineering, with at least 5+ years in a leadership role driving regional or global practices.
  • Hands-on experience with Guidewire testing and insurance domain processes.
  • Deep expertise in full-stack test automation:
    Web, API, Mobile/Digital, Database, and TDM solutions.
  • Strong exposure to AI/ML-based quality engineering practices – predictive analytics, autonomous AI for QE, self-healing automation, and intelligent test data management.
  • Experience in Multi-Agent Orchestration Systems across STLC, leveraging Agentic AI solutions, RAG (Retrieval-Augmented Generation), and LLMs for intelligent automation.
  • Ability to design and implement AI-driven workflows for user story refinement, test case generation, and automation script creation, ensuring measurable optimization and acceleration in QE processes.
  • Hands-on experience in setting up MCP (Model Context Protocol) servers to enable secure, scalable orchestration of AI agents across STLC phases, integrating context-aware prompts and multi-agent collaboration for QE automation.
  • Proven experience in technical consulting, solutioning, and assessments for large enterprise clients.
  • Strong background in pre-sales, RFPs, solution architecture, and business consulting.
  • Demonstrated ability to convert opportunities into revenue, aligning technical delivery with business outcomes.
  • Excellent client-facing, stakeholder management, and communication skills with the ability to influence CXO-level discussions.
  • Strong understanding of modern delivery models (Agile, Dev Ops, CI/CD, Cloud-native, Microservices).
  • Experience in building Center of Excellence (CoE) and driving knowledge sharing, accelerators, and IP creation.
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