招聘
Benefits & Perks
•Flexible Hours
•Flexible Hours
Required Skills
Python
Generative AI
Large Language Models
Prompt engineering
Testing frameworks
We are seeking someone to join our team as a Generative AI Engineer within Finance Technology, developing Gen AI–driven solutions that support core Finance functions across the firm, including systems supporting PnL, Capital, Liquidity, Regulatory and Balance Sheet.
In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Software Engineer position, which is part of the job family responsible for developing and maintaining software solutions that support business needs.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
What you’ll do in the role:
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Work as part of an engineering team developing Gen AI–driven solutions for Finance Technology.
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Design and develop a generative AI–driven chatbot tailored to core finance analytical functions, enabling it to handle a wide range of finance-related user queries (e.g., liquidity stress testing, balance sheet, collateral management, deposits, positions).
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Develop and enhance an agentic analysis solution to perform multi-step financial analysis and processing, including data querying, variance analysis, data quality analysis, and python/pandas code generation and execution.
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Develop and refine a testing framework to assess the performance of AI agents used for financial analysis.
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Create, test, and fine-tune prompt-generation strategies to improve large language model performance and enhance the chatbot’s accuracy and relevance in financial contexts.
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Develop and maintain the infrastructure required to deploy and scale the chatbot, building on the firm’s AI infrastructure and services while meeting performance and security requirements.
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Integrate the chatbot with existing financial systems and databases to provide real-time insights and accurate information to users.
What you’ll bring to the role:
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Deep hands-on expertise in Python, in a financial services environment is a plus.
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Exposure to, experience with, or strong interest in working on generative AI–driven solutions for Finance Technology as part of an engineering team.
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Exposure to, experience with, or interest in developing and enhancing agentic analysis for multi-step financial analysis and processing, including data querying, variance analysis, data quality analysis, and python/pandas code generation and execution.
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Experience developing and refining a testing framework to assess performance, ideally in the context of AI-enabled financial analysis.
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Exposure to, experience with, or interest in creating, testing, and fine-tuning prompt-generation strategies to improve large language model performance and enhance accuracy and relevance in financial contexts.
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Exposure to, experience with, or interest in developing and maintaining infrastructure for deploying and scaling a chatbot on the firm’s AI infrastructure and services, meeting performance and security requirements.
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Exposure to, experience with, or interest in integrating AI solutions with existing financial systems and databases to provide real-time insights and accurate information to users.
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Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
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.
Certified Persons Regulatory Requirements: If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks.
Flexible work statement
Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.
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About Morgan Stanley

Morgan Stanley
PublicA financial services company that offers securities, asset management, and credit services.
10,001+
Employees
New York
Headquarters
Reviews
3.5
4 reviews
Work Life Balance
3.0
Compensation
2.5
Culture
3.2
Career
3.0
Management
3.0
35%
Recommend to a Friend
Pros
Skills evaluation through business plans and projects
Direct access to senior leadership interviews
Conversational interview format
Cons
Automated resume screening system issues
Focus on formatting over qualifications
Compensation concerns and salary expectations
Salary Ranges
11,766 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
1,682 reports
$114,371
total / year
Base
$96,366
Stock
-
Bonus
$18,005
$77,808
$170,800
Interview Experience
6 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Experience
Positive 16%
Neutral 84%
Negative 0%
Interview Process
1
Initial screening (HR/HireVue)
2
Technical rounds
3
Manager/Senior leadership interviews
4
Final round/Superday
Common Questions
Technical knowledge assessment
Behavioral questions
Role-specific scenarios
Leadership and teamwork examples
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