{"id":1717123,"url":"https://alion.io/job/accenture-qa-lead-ai-augmented","title":"QA Lead - AI Augmented","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2001,"ghost_share":0.001,"stale_share":0.08,"repost_share":0.005,"time_to_fill_p50_days":5,"computed_at":"2026-10-13T05:45:00Z"}},"role":"QA","role_family":"QA","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ebène, Mauritius"],"countries":["MU"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Scrum","optional":false},{"name":"Shift-Left","optional":false},{"name":"Shift-Left Security","optional":false}],"status":"live","first_seen_at":"2026-10-02T19:00:00Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-13T03:17:51Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"The QA Lead - QA Strategist & AI-Augmented Quality drives the overall quality strategy across the delivery lifecycle, embedding quality from requirements through production rather than limiting QA to test execution.\nThe role combines Quality Engineering, strategic QA governance, risk-based testing, people leadership, stakeholder management, and AI-augmented quality practices.\nActing as a Quality Strategist and Quality Assurer, the QA Lead challenges requirements, identifies risks early, defines the appropriate quality approach, and enables teams to build quality by design.\nAI is leveraged to augment QA expertise, improve efficiency and coverage, accelerate analysis, and generate quality insights, while maintaining human ownership, judgement, and validation.\nKey Responsibilities:\nQA Strategy & Quality Engineering\nDefine and drive the QA strategy aligned with business objectives, product risks, architecture, and delivery methodology.\nEstablish testing approaches, quality gates, coverage objectives, environments, data, and release criteria.\nApply Risk-Based Testing to prioritise QA efforts according to business and technical risk.\nPromote Quality Engineering, shift-left, and quality-by-design practices.\nContinuously improve QA processes, standards, frameworks, and ways of working.\nDefine test scenarios and conditions based on business and technical risks.\nEnsure appropriate use of test techniques including EP, BVA, Decision Tables, State Transition, Error Guessing, Exploratory Testing, and Risk-Based Testing.\nOversee functional, integration, regression, UAT, API, exploratory, and end-to-end testing.\nLead defect triage and monitor quality risks, coverage, and defect trends.\nProvide objective quality information to support release readiness and Go/No-Go decisions.\nStrategic Shift-Left\nEngage early in requirements, solution, and design discussions.\nReview BRDs, user stories, acceptance criteria, and functional specifications from a quality perspective.\nChallenge ambiguous, incomplete, contradictory, or non-testable requirements.\nIdentify functional and business risks before development.\nPromote 3 Amigos collaboration between Business, Development, and QA.\nFocus on defect prevention, not only defect detection.\nAI-Driven Quality Intelligence\nDefine and promote the use of AI across QA activities.\nLeverage AI in the testing activities.\nUse AI to identify quality gaps, recurring defects, abnormal patterns, and potential risks.\nEstablish human validation of AI-generated outputs.\nPromote prompt engineering and AI-assisted problem solving within QA teams.\nEnsure responsible use of AI, including consideration of data privacy, limitations, accuracy, and human oversight.\nMove QA towards predictive and preventive quality using data, historical defects, production incidents, and AI-assisted analysis.\nIdentify opportunities to optimise regression scope and testing priorities.\nUse AI-assisted insights to support quality dashboards and management reporting.\nEstablish feedback loops between production, defects, testing, and future QA strategies.\nPeople Leadership\nLead, coach, mentor, and develop QA Engineers and Analysts.\nBuild QA capability across testing, automation, Quality Engineering, and AI.\nDefine competency expectations and development plans.\nPromote knowledge sharing and continuous learning.\nFoster a culture where QA professionals are empowered to challenge requirements and raise risks.\nStakeholder & Client Management\nAct as a senior QA contact for Business, Product, Development, Architecture, Operations, and clients.\nCommunicate quality status, risks, dependencies, and release readiness.\nTranslate technical quality risks into business impact.\nFacilitate quality discussions and challenge delivery decisions where necessary.\nSupport governance meetings, client presentations, audits, and quality reviews.\nQuality Governance\nDefine and maintain QA standards, processes, templates, and best practices.\nEstablish quality governance across projects and teams.\nTrack and analyse quality metrics such as defect leakage, coverage, regression effectiveness, defect ageing, automation coverage, and production incidents.\nProvide quality reporting to management.\nDrive continuous improvement based on measurable quality outcomes.\n\nRequired Qualifications\nBachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field.\nCertifications in Quality Assurance, Testing, or Agile methodologies would be advantageous, such as: ISTQB Foundation/Advanced Level Certified Agile Tester (CAT) Scrum Master or Agile certifications Quality Engineering certifications\nExtensive experience in Software Testing, Quality Assurance, or Quality Engineering.\nProven experience leading QA teams and managing complex testing initiatives.\nExperience working in Agile, Scrum, and DevOps environments.\nExposure to AI-assisted testing tools and AI-enabled quality practices.\nAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, militaryveteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicablelaw. 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