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Quality Engineering Practice Lead

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Jobtailor
Full Time position
Listed on 2026-09-13
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Business & Operations
Salary/Wage Range or Industry Benchmark: 90000 - 130000 GBP Yearly GBP 90000.00 130000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

  • Provide technical leadership and governance across modern Quality Engineering practices
  • Act as senior technical authority for complex client engagements and significant Quality Engineering challenges
  • Own and evolve the Quality Engineering capability strategy, roadmap and service portfolio
  • Maintain relevant standards, methodologies, reference architectures and reusable assets
  • Define viewpoints on emerging developments and identify capabilities for investment or market development
  • Establish communities that share expertise and innovation
  • Shape Quality Engineering opportunities through client conversations, discovery workshops, proposals and commercial solution design
  • Remain hands-on and partially billable where required through direct client engagement
  • Establish new Quality Engineering services and prove value in early-stage opportunities
  • Develop differentiated, outcome-led Quality Engineering propositions and support account growth
  • Advise clients, build trusted relationships and facilitate executive briefings, workshops and maturity assessments
  • Strengthen market presence through conferences, webinars, round tables and thought‑leadership content
  • Develop technical career paths, competency frameworks and future‑skills programmes
  • Coach emerging leaders, develop subject matter experts and support talent attraction
  • Foster knowledge sharing, experimentation, continuous professional development, technical excellence, curiosity and innovation
  • Lead the approach to AI across Digital Assurance
  • Identify practical applications of generative AI, machine learning and agentic AI
  • Translate concepts into repeatable, commercially viable services and accelerators
  • Shape approaches for testing, validating and monitoring AI systems
  • Encourage disciplined experimentation that delivers measurable value
Requirements
  • Significant experience within software Quality Engineering, testing or Digital Assurance
  • Strong technical understanding of modern test automation approaches, architectures and frameworks
  • Strong knowledge of performance testing and performance engineering
  • Experience with modern Agile, Dev Ops and CI/CD delivery models
  • Experience defining Quality Engineering strategies, frameworks or technical standards
  • Strong understanding of generative AI and related technologies in software engineering and Quality Engineering
  • Practical understanding of opportunities, limitations and risks of AI‑enabled testing
  • Understanding of testing and assuring AI‑based systems
  • Demonstrable curiosity about emerging technology and its practical application
  • Experience in consultancy, professional services, technology services or a similarly client‑facing environment
  • Strong client‑facing communication and stakeholder‑management capability
  • Experience shaping solutions during pre‑sales activities
  • Experience contributing to proposals, bids, presentations or commercial solutions
  • Ability to translate technical concepts into compelling business outcomes
  • Confidence engaging with senior technology and business stakeholders
  • Experience leading technical teams, capabilities, communities or practices
  • Strong coaching, mentoring and people‑development skills
  • Ability to influence across organisational boundaries without relying solely on formal authority
  • Experience developing capability through others
  • Ability to establish a clear technical vision and bring people with them
  • AI Assurance, Responsible AI or AI governance
  • Agentic AI or autonomous software engineering approaches
  • AI/ML model validation and testing
  • AI governance frameworks such as ISO/IEC 42001 or regulatory frameworks including the EU AI Act
  • Building technical accelerators, frameworks, platforms or reusable intellectual property
  • Conference speaking, publishing or recognised industry thought leadership
  • Building or scaling an…
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