Lead QA Engineer AI_Vice President_QA Engineering

About

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries.
As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethics. Morgan Stanley can provide a superior foundation for building a professional career – a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Divisional Overview

Wealth Management and Investment Management Technology (WMIMT) are responsible for the design, development, delivery and support of the technical platform behind the products and services used by Morgan Stanley Business.

Project Description

As a Quality Engineer specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft, taking a hands‑on approach to multiple high‑visibility projects with the following responsibilities:

Responsibilities

• Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop quality engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, AI-driven test automations.
• Technical Leadership and Advocacy: Serve as the quality advocate for products, ensuring high-quality automation coverage, appropriateness, feasibility, and alignment with business and customer goals. Design, develop, and maintain advanced automation frameworks to drive Automation first mindset using advanced techniques including BDD, AI and GenAI technologies to streamline and enhance the testing process.
• Engineering Craftsmanship: Maintain accountability for the integrity of test design, test automation, their ongoing maintenance and scale, as well as the quality of solutions. Stay hands‑on, self‑driven, and continuously learn new approaches, tools, techniques, and frameworks. Integrate AI and GenAI tools and techniques into existing testing processes to improve accuracy, efficiency, and coverage of automated tests.
• Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning‑forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
• Advanced Technical Proficiency: Possess basic knowledge of modern quality engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using techniques like fully automated in‑sprint testing to accept the stories and work products, powered by AI/GenAI, throughout the SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate an understanding of the full lifecycle product development, focusing on continuous improvement and learning.
• Domain Expertise: Quickly acquire domain‑specific knowledge relevant to the business or product. Translate business/user needs and UX/UI designs into test automation. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.

The candidate should be flexible, highly adaptable and an excellent team player. The role requires credibility and confidence interacting with senior management, business unit personnel, branch offices and the technology team across the full lifecycle of a project. The candidate should expect to work with global team along with US and India team members, sometimes across multiple time zones. The ideal candidate will be a self‑motivated team player committed to delivering on time and should be able to work under minimal supervision.

Qualifications

• 10+ years of proven work experience in Quality Engineering.
• Experience with AI/GenAI tools and frameworks (e.g., TensorFlow, PyTorch, OpenAI, Python, etc.).
• Integrate LLM automation tests into the continuous integration and continuous deployment pipelines. Hands‑on experience in LLM implementation and agentic orchestration.
• Proven experience in developing and implementing automation frameworks for Large Language Models. Strong programming skills in languages such as Python, Java, or similar.
• Understanding of Agentic AI is a must. Should have the knowledge in agentic orchestration frameworks like LangChain, LangGraph, OpenAI SDK etc.
• Experience with coding assistants such as GitHub Copilot, Cursor.
• Hands on experience in implementing Chain of Evaluation, Chain of Thought strategies in LLM evaluation.
• Evaluation techniques such as LLM as a Judge is a plus.
• Understanding of RAG Technique.
• Hands‑on experience in assessing the capacity of Kafka for asynchronous processing.
• Expert with CI/CD pipelines and version control systems (e.g., Jenkins, TeamCity, Git).
• Strong problem‑solving and analytical skills.
• Experience in automation technologies including Playwright, Selenium, Junit, Gherkin, JMeter etc. and scripting languages including java, python.
• Solid foundation in modern, front‑end technologies, including TypeScript, HTML/CSS, and web frameworks like React or Node.js.
• Experience with API development and cloud computing platforms, specifically Azure (experience with MCP Servers a big plus).
• Proficiency in usage of PostgreSQL and Vector databases (Redis) or large datasets.
• Ongoing monitoring using Splunk, Grafana.
• Team player with good communication skills to work effectively in a global team.

What You Can Expect from Morgan Stanley

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values – putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back – aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work‑life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.

Equal Opportunity Statement

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross‑section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.