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.

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