Senior Principal Engineer - IT Quality & Assurance Testing

Marsh McLennan is hiring a Senior Principal Engineer - 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 lead role.
Marsh McLennan has 651 other open roles on Level.
Posted in the last few days.

AI in this role

prompt-engineeringragai-agentsai-evaluationai-safety

Company:

Marsh

Description:

We are seeking a talented individual to join our MMB LAC L3 Squad team at Marsh People and Investments, a Marsh business. This role will be based in Pune/Gurugram. This is a hybrid role that has a requirement of working at least three days a week in the office.

Your Experience:

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.

Things you will do:

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 you will bring:

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.

Values and Culture:

Our team comprises all sorts of people from all sorts of backgrounds. We believe everyone brings value and a unique perspective and want to promote a fun and diverse culture. To help us succeed we hope that you can demonstrate:

A genuine passion for technology
A clear commitment to creating brilliant products that will give our clients the edge
A willingness to work fluidly and respectfully with our talented team

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to providing an inclusive work environment. We aim to attract and retain the best, most qualified people and value colleagues of all backgrounds, without regard to age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

How we rate this

Senior Principal Engineer - 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.

Classification

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.

Key facts

Senior Principal Engineer - IT Quality & Assurance Testing is an open job at Marsh McLennan.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Gurugram - DLF Building.
The job was posted on November 13, 2026.
Seniority: lead.
Applications are handled by Marsh McLennan. Apply on Marsh McLennan

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agentsAI EvaluationAI Safety

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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