Manager - IT Quality & Assurance Testing
Marsh McLennan is hiring a Manager - IT Quality & Assurance Testing in Gurugram, India. Level rates it ; you can apply on Marsh McLennan.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions prompt engineering, RAG and AI agents among its tools and skills.
- Level classes it as a senior role.
- Marsh McLennan has 627 other open roles on Level.
- Posted in the last few days.
AI in this role
Company:
MarshDescription:
We are seeking a talented individual to join our Tech Team at Marsh. This role will be based in Gurugram.This is a hybrid role that has a requirement of working at least three days a week in the office.This role will be based in Gurgaon. This is a hybrid role that has a requirement of working at least three days a week in the office
Manager – Quality / AI Assurance
We will count on you to:
A visionary forward thinker who views Quality holistically and can drive a Quality Engineering mindset across traditional software and AI-powered applications. Understanding industry trends, tools and practices and implementing the right approaches to deliver high-quality, scalable and reliable software.
- 10+ years' experience in Software Testing / Quality Engineering with experience in managing end-to-end project delivery.
- Proven experience leading QA teams across Manual, Automation and AI/LLM testing.
- Strong understanding of STLC, SDLC, Agile, test strategy, test planning, risk management, defect management and quality metrics.
- Experience defining testing strategies for Web/UI, API, Database, AI/LLM, RAG and AI-powered applications.
- Strong automation experience using Python, JavaScript/TypeScript, Java, Playwright, Selenium and WebdriverIO (WDIO).
- Good understanding of API testing, SQL, relational databases and data validation.
- Understanding of RAG architecture, embeddings, vector databases, semantic search, retrieval and reranking.
- Experience with Generative AI, LLM evaluation, prompt engineering, AI agents and AI safety testing.
- Experience with AI/LLM testing and evaluation frameworks such as PromptFoo, Ragas, DeepEval, LangSmith and PyRIT, or similar tools.
- Strong understanding of AI quality and security risks including prompt injection, jailbreaks, hallucination, data leakage, guardrails and responsible AI.
- Experience with modern DevOps and test automation practices, including Git, GitHub, GitHub Actions and CI/CD pipeline integration.
- Strong communication, stakeholder management, analytical and people leadership skills.
What you need to have:
- Input into planning and subsequent resource planning – including skills profiling and identifying training requirements for team members.
- Define and drive the Quality Engineering, Automation and AI Testing strategy across projects.
- Lead testing across UI, API, Database, Automation and AI/LLM applications.
- Establish AI testing and evaluation practices covering accuracy, relevance, faithfulness, groundedness, hallucination, safety and security.
- Drive testing of RAG applications, vector databases, retrieval pipelines, prompts and AI agent workflows.
- Evaluate and adopt appropriate AI testing, evaluation, observability and security tools based on project requirements.
- Lead automation initiatives using Playwright, WebdriverIO, JavaScript/TypeScript and Java, integrated with CI/CD and GitHub Actions.
- Establish scalable and maintainable automation frameworks, reusable utilities and test assets.
- Define and monitor test coverage, automation coverage, AI evaluation metrics, defect leakage and release quality.
- Drive shift-left testing, continuous testing, risk-based testing and quality engineering practices.
- Ensure effective root cause analysis, defect prevention and continuous quality improvement.
- Mentor and develop QA engineers across manual testing, automation and AI testing.
- Work closely with Product, Engineering, AI/ML, Data Science, Security and Business teams.
- Manage team performance, delivery risks, conflicts and stakeholder expectations.
- Ensure consistent testing standards, processes and quality practices across teams.
What makes you stand out:
- Minimum 12 months experience as Senior Principal Engineer
- Should have at least “On-Track” or equivalent rating in last appraisal.
- Should not be under any Performance Counselling Plan or have any official disciplinary action within the last 3 month
- Strong understanding of Quality Engineering, Manual Testing, Automation and AI/LLM Testing.
- Strong experience with Playwright, WebdriverIO/Selenium, Python, JavaScript/TypeScript and Java.
- Good knowledge of UI, API, SQL/Database and data validation testing.
- Understanding of RAG, embeddings, vector databases, semantic search, retrieval and LLM evaluation.
- Experience with AI/LLM evaluation and testing tools such as PromptFoo, Ragas, DeepEval, LangSmith and PyRIT.
- Understanding of AI security, prompt injection, jailbreaks, hallucination, guardrails, red-team testing and responsible AI.
- Experience with GitHub and CI/CD pipelines.
- Experience building and maintaining scalable automation frameworks.
- Proven experience managing, mentoring and developing QA/Quality Engineering teams.
- Strong communication, stakeholder management, analytical and problem-solving skills.
- Ability to evaluate emerging technologies and introduce effective testing solutions.
- Passion for AI, automation, Quality Engineering and continuous improvement.
Why join our team:
- We help you be your best through professional development opportunities, interesting work and supportive leaders.
- We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
- Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
How we rate this
Manager - IT Quality & Assurance Testing at Marsh McLennan rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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