Job Description
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.
- 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.
- 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.
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