Automation Testing - SDET

Zensar•Princeton, NJ

1d•Remote

About The Position

We are seeking a QE Architect – BFS to lead Quality Engineering initiatives for Banking and Financial Services clients. This role demands expertise in BFS domain testing, full-stack automation, and strategic consulting to deliver measurable business outcomes.

Requirements

15+ years in Software Testing, Test Automation, and Quality Engineering, with 5+ years in leadership roles driving regional/global practices.
Strong BFS domain knowledge: core banking, payments, fraud detection.
Deep expertise in full-stack test automation: Web, API, Mobile/Digital, Database, and TDM solutions.
Proven exposure to AI/ML-based QE practices: predictive analytics, autonomous AI for QE, self-healing automation.
Experience in Multi-Agent Orchestration Systems across STLC, leveraging Agentic AI, RAG, and LLMs for intelligent automation.
Ability to design AI-driven workflows for user story refinement, test case generation, and automation script creation.
Hands-on experience in setting up MCP (Model Context Protocol) servers for secure orchestration of AI agents across STLC phases.
Strong background in technical consulting, solutioning, and assessments for large enterprise clients.
Expertise in pre-sales, RFPs, solution architecture, and business consulting.
Excellent client-facing and stakeholder management skills, with ability to influence CXO-level discussions.
Strong understanding of Agile, DevOps, CI/CD, Cloud-native, and Microservices delivery models.
Experience in building Centers of Excellence (CoE) and driving knowledge sharing, accelerators, and IP creation.

Responsibilities

Architect and implement full-stack automation frameworks for BFS applications (Web, Mobile, API, Database).
Drive risk-based testing, security, and performance validation for BFS platforms.
Provide consulting on compliance, regulatory requirements, and digital banking transformation.
Participate in client consulting engagements and deliver high-impact recommendations for quality transformation.
Prepare solution approaches, proposals, and technical statements of work (SoW) tailored to client needs.
Champion AI/ML-based quality engineering approaches: predictive analytics, intelligent test design, and self-healing automation.
Drive Test Data Management (TDM) strategies for robust and scalable test environments.
Support new business pursuits, RFPs, RFIs, and proactive proposals with strong solution leadership.
Collaborate with sales and account teams to position Quality Engineering as a business differentiator.
Define and track metrics linking automation and AI-led solutions to client ROI and revenue outcomes.
Mentor and coach high-performing engineering teams across the US region.
Foster a culture of innovation, continuous improvement, and cross-collaboration.
Partner with global practice leaders to ensure alignment and knowledge sharing across geographies.