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Guidewire QE Solution Architect – Insurance Leader
Job in
Princeton, Mercer County, New Jersey, 08543, USA
Listed on 2026-02-10
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-OverviewRole-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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