Enterprise Test Strategy & QE Transformation Lead

Role Overview

We are looking for a senior Quality Engineering leader to lead enterprise-level test strategy and QE transformation assessments for a large, complex client environment. This is a client‑facing leadership role. The person will interact directly with senior client stakeholders, lead the current‑state assessment, define the future‑state quality engineering vision, and build a comprehensive, executable Enterprise Test Strategy that can move directly into implementation.

The ideal candidate has done this before, has led structured QE assessments, facilitated senior stakeholder workshops, diagnosed enterprise testing challenges, built defensible transformation roadmaps, and produced strategy artifacts that clients can actually operate from.

• Lead enterprise Quality Engineering assessments across large, complex organizations with multiple business units, applications, technology stacks, and delivery models.
• Run structured discovery activities, including stakeholder interviews, current‑state process mapping, tooling inventory, artifact reviews, and maturity assessments across QE and adjacent engineering functions.
• Facilitate on‑site workshops with CTOs, QE leaders, technology executives, BU testing leads, product teams, engineering teams, and business stakeholders.
• Build evidence‑backed, concrete findings versus generic – for example, diagnosing why testing lags, why automation is not scaling, where UAT/SIT boundaries are unclear, or where tooling/process fragmentation is creating delivery risk.
• Assess current‑state maturity across key QE domains, including test automation, AI‑enabled testing, performance engineering, test data management, Dev Ops/CI‑CD integration, governance, tooling, and operating model.
• Produce core diagnostic artifacts such as quality maturity heatmaps, risk‑based test prioritization models, UAT/SIT boundary analysis, automation maturity views, tooling rationalization analysis, and QE operating model recommendations.
• Define the future‑state quality engineering vision, governance model, delivery model, and prioritized transformation roadmap in partnership with the client.
• Build a Master Enterprise Test Strategy covering Agentic AI, AI/GenAI Assurance, automation, AI‑enabled testing, performance, test data management, Dev Ops integration, quality governance, metrics, people/process/culture, and business‑unit adoption.
• Define outcome‑based KPIs and metrics frameworks tied to business outcomes, quality improvement, delivery acceleration, risk reduction, and maturity uplift – not just activity counts.
• Develop RACI models, governance structures, and operating models for Quality Centers of Excellence, embedded QE teams, business‑unit testing teams, and shared services.
• Translate findings into a practical Design‑phase roadmap with named deliverables, sequencing, ownership, dependencies, and visible quick‑win opportunities within the first 30 days.
• Co‑present findings and recommendations directly to senior client stakeholders and defend the diagnosis under challenge or pushback.
• Partner with solution, account, and delivery teams to ensure the roadmap is realistic, executable, and grounded in what was actually discovered.
• Hand off a prioritised, phased execution roadmap into implementation, ensuring continuity between assessment findings and delivery outcomes.
• Lead the implementation of newly defined Enterprise Test Strategy during the steady state in the role of an Enterprise Test Architect.

• 15+ years of experience in software quality engineering, QA transformation, enterprise testing, or related technology delivery leadership roles.
• Proven experience leading enterprise QE strategy, test strategy, quality transformation, or assessment engagements for large organizations.
• Strong background across the full quality engineering landscape, including test automation, in‑sprint automation, AI‑enabled testing, performance testing, test data management, Dev Ops/CI‑CD, UAT/SIT design, and QE governance.
• Strong working awareness of AI/GenAI in Quality Engineering, including where it can accelerate testing outcomes and where foundational QE practices, data quality,…