QA Thoughtleader/Director

• Define the QA managed services offering, including service catalog, operating model, SLAs/KPIs, transition-to-steady-state approach, and outcome-based engagement models.
• Build differentiated QA accelerators, reusable IP, AI-enabled testing frameworks, and tooling that improve speed, quality, cost efficiency, and margin.
• Partner with Business Development and sales teams on RFP responses, client solutioning, deal-room positioning, pricing models, and commercial shaping.
• Lead the evolution of AI-native quality engineering by translating AI capabilities into new delivery economics, pyramid compression, productivity gains, and outcome-based commercials.
• Govern execution through delivery teams and project managers while retaining accountability for quality, client confidence, margin, and practice-level outcomes.
• Build the practice from zero to scale by establishing methods, playbooks, delivery standards, talent models, and go-to-market narratives.
• Represent the organization as a credible QA thought leader in client conversations, solution workshops, proposals, and strategic pursuits.

Ideal Candidate Profile

• Has operated as a Offering Lead, Head of Testing Services, Director of Quality Engineering Services, QE Solutions Lead, or equivalent role.
• Has defined or built a QA/QE managed services offering, not merely managed delivery within an existing account or framework.
• Understands managed services commercials, including SLA/KPI-based models, outcome-based pricing, margin ownership, pyramid structure, and transition-to-steady-state models.
• Has demonstrated AI-native quality engineering thinking, with clear examples of AI improving unit economics, productivity, margin or commercial differentiation.
• Has built reusable accelerators, frameworks, tools, platforms or IP that directly improved win rate, delivery efficiency, or profitability.
• Has strong presales and solutioning experience, including RFPs, client workshops, proposal shaping, commercial models and executive-level client conversations.
• Has the builder mindset required to create a new practice, service line or GTM motion from scratch.

Required Experience

• 15+ years of experience in Quality Engineering, QA transformation, testing services, or managed services leadership.
• Experience leading or shaping QA/QE service offerings for external clients, preferably within an IT services, specialist testing, digital engineering, or consulting environment.
• Strong exposure to AI/GenAI-led testing, automation, self-healing frameworks, intelligent test design, test data, observability, or productivity-led QA transformation.
• Proven experience in solutioning, deal support, RFP responses, pricing inputs, and commercial conversations.
• Track record of building or scaling practices, service lines, accelerators, reusable assets, or capability centers.
• Experience owning or influencing practice-level P&L, margins, delivery economics, or revenue growth is strongly preferred.

Must-Have Selection Criteria

• AI-native QE conviction:

  The candidate must explain how AI changes the commercial model of QA managed services, not just list tools.

• Managed-services business model ownership:

  The candidate must have defined offerings, SLAs/KPIs, accelerators, transition models, and commercial structures.

• Build-from-zero practice posture:

  The candidate must have created or scaled a new practice, service line, accelerator, or GTM capability.