Description
About Alvarez & Marsal
Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging workguided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity - are why our people love working at A&M.
The Team
Our DTS team covers the full breadth of Technology Consulting and M&A services, including -
- Technology M&A and Strategy - Assist clients to manage the technology aspects and business enablement of complex M&A, integrations and carve-outs as well as post-deal value creation
- Technology Consulting End to end technology advisory for clients, including developing technology roadmaps, platform/cloud/data advisory as well as transformation excellence for a digital transformation
- Data & AI services - Helping clients in harnessing the power of data and cutting-edge analytics to drive intelligent decision-making and transform businesses.
- Develop GenAI and Agentic AI solutions that create real business value for clients through process re-invention
How You Will Contribute
The
Lead QA / Quality Engineering Lead is a critical role responsible for defining and enforcing
end-to-end quality standards across AI, Data, and Generative AI solutions. This role operates at the intersection of
quality engineering, AI model validation, data correctness, and enterprise release governance, ensuring that AI systems are
accurate, reliable, safe, and production-ready before being exposed to business users. This role exists to prevent failures by embedding
AI-aware quality engineering practices, automation, and rigorous validation into the delivery lifecycle.
Key Responsibilities
- Quality Strategy & QA Governance
- Define and own the quality engineering strategy for AI, Data, and GenAI platforms
- Establish QA standards, test frameworks, and quality gates across data pipelines, AI/ML models, GenAI prompts and workflows, and application services
- Embed quality checkpoints into CI/CD pipelines and release processes
- Partner with GenAI & Data Solution Architects to ensure quality is addressed by design
- AI & GenAI Testing
- Define and execute AI-specific testing strategies including hallucination detection, prompt drift and regression testing, model consistency, and adversarial scenarios
- Design and validate test cases for RAG pipelines, agentic workflows, tool calling, and context/memory handling
- Validate correctness, explainability, and transparency of AI outputs
- Perform end-to-end testing across UI (React), backend services (Python), vector databases, and LLM-powered workflows
- Build and maintain Python-based automation frameworks using PyTest, Selenium/Playwright, and Requests
- Implement automated API testing with schema validation, database checks, and error-handling scenarios
- Integrate automated tests into CI/CD pipelines and generate execution and quality reports
- Troubleshoot failures using application logs, backend logs, and model inference logs and drive root-cause resolution
- Data Quality & Validation
- Define and enforce data quality standards for accuracy, completeness, consistency, and timeliness
- Validate data pipelines supporting analytics, ML, and GenAI systems
- Perform data reconciliation, profiling, and anomaly detection using SQL and related tools
- Partner with data engineering teams to identify and resolve data issues early
- Test Automation & Tooling
- Design and implement automated testing frameworks covering unit, API, integration, and UI testing
- Ensure automation supports frequent releases without compromising quality
- Maintain test coverage for AI features including embeddings, vector stores, RAG pipelines, and prompt orchestration
- Functional, Integration & UAT
- Lead functional, integration, system, and regression testing activities
- Coordinate User Acceptance Testing (UAT) with business stakeholders
- Ensure UAT scenarios reflect real-world AI and business usage
- Track defects, prioritize fixes, and validate resolutions prior to release sign-off
- Observability, Reliability & Defect Management
- Implement quality-focused observability to detect AI output regressions, performance degradation, and error trends
- Analyze production defects and quality incidents
- Lead root-cause analysis (RCA) and corrective actions
- Partner with DevOps and Platform teams to support shift-left testing and monitoring
- Release Readiness & Compliance
- Define and enforce release readiness criteria for AI and data platforms
- Provide quality sign-off for production releases, model and prompt deployments, and feature rollouts
- Ensure alignment with enterprise governance, security, compliance, and Responsible AI principles
- Collaboration & Leadership
- Collaborate with architects, AI engineers, data teams, platform engineers, product owners, and delivery teams
- Participate actively in Agile ceremonies and sprint planning
- Provide technical leadership and mentoring to QA engineers
- Promote a quality-first culture and scale GenAI-specific testing practices
Qualifications
- 812+ years of experience in Quality Assurance or Quality Engineering
- Proven experience leading QA for complex, enterprise-scale platforms
- Strong experience testing data-intensive, AI/ML, or GenAI-based systems
- Hands-on experience leading QA teams and automation initiatives
- Strong experience with test automation tools (Selenium, Playwright, Katalon) and API testing frameworks
- Proficiency in Python-based automation (PyTest, Requests) and backend/API validation
- Strong SQL and NoSQL (MongoDB) skills for data validation and reconciliation
- Experience testing modern web applications (React preferred)
- Familiarity with GenAI systems including RAG pipelines, embeddings, vector databases, prompt flows, and model APIs
- Experience with cloud platforms (Azure or AWS), CI/CD pipelines, and automated release testing
- Ability to analyze logs, debug failures, and work across engineering teams
- Understanding of AI evaluation metrics, hallucination detection, and prompt testing techniques
- Strong attention to detail with a focus on risk prevention and impact
- Analytical mindset for identifying patterns and root causes
- Ability to clearly communicate quality risks to technical and business stakeholder
- Collaborative approach with engineering and product team
- Strong ownership mindset with bias toward prevention over detection
Your journey at A&M
We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person's unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career. We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.
Inclusive Diversity
A&M's entrepreneurial culture celebrates independent thinkers and doers who can positively impact our clients and shape our industry. The collaborative environment and engaging workguided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversityare the main reasons our people love working at A&M. Inclusive Diversity means we embrace diversity, and we foster inclusiveness, encouraging everyone to bring their whole self to work each day. It runs through how we recruit, develop employees, conduct business, support clients, and partner with vendors. It is the A&M way.
Equal Opportunity Employer
It is Alvarez & Marsal's practice to provide and promote equal opportunity in employment, compensation, and other terms and conditions of employment without discrimination because of race, color, creed, religion, national origin, ancestry, citizenship status, sex or gender, gender identity or gender expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, family medical history, genetic information or other protected medical condition, political affiliation, or any other characteristic protected by and in accordance with applicable laws. Employees and Applicants can find A&M policy statements and additional information by region here.
Unsolicited Resumes from Third-Party Recruiters
Please note that as per A&M policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that A&M will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
