Senior AI Solutions Engineer VP - P4
1 New York Plaza, United States
Full Time Senior-level / Expert USD 150K - 210K
Morgan Stanley
Discover how we help individuals, families, institutions and governments raise, manage and distribute the capital they need to achieve their goals.Department Profile: Firmwide Data Office (FDO)
The Firmwide Data Office (āFDOā) sits within Morgan Stanley Technology and focuses on data as a key priority within the overall Technology and the Firm strategy.
We are a team of around 200+ people distributed globally and are engaged in a wide array of projects touching all business units (Institutional Securities, Investment Management, Wealth Management) and functions (e.g., Operations, Finance, Risk, Trading, Treasury, Resilience, Production Management) across the Firm. The team vision is a multi-year effort to improve data governance & management practices, to demonstrate data quality controls, simplify firmās data architecture and business processes front-to-back, empowering developers by providing consistent means of handling data, facilitate data-driven insights & decision making.
Program Description:
We are working on an exciting new initiative to build an Enterprise Knowledge Graph by harnessing the power of Graph and Semantic technologies along with LLMs, and Agentic AI to map complex business, application, data, and infrastructure asset relationships to facilitate data-driven insights and decision making.
Across our business divisions, as we strive to understand risk impact, optimize cost, assess business resiliency, manage change, and identify opportunities - all critical to fuel the growth engine -, we need to link vast amount of data of different types and forms across heterogeneous data sources across the Firm to generate meaningful intelligence. The underlying data will describe the Firmās businesses, business processes and various operational assets required to support those businesses (systems, technology infrastructure, datacenter facilities, workforce, workforce facilities, external supplier services and industry utilities).
Role
The āFirmwide Data Officeā department is recruiting for an enthusiastic, dynamic, hands-on and delivery focused AI Solutions Engineer with a strong background in working with Generative AI(GenAI), Large Language Models (LLMs), traditional AI, and Natural Language Processing (NLP) techniques. The ideal candidate, in addition to experience in data science, will possess expertise in designing, architecting, and optimising data-intensive systems, with a keen focus on big data analytics. This role offers exciting opportunity to work on cutting-edge projects leveraging LLMs with large volumes of structured and unstructured data as well as building and integrating Knowledge Graph, LLMs and Multiagent systems.
As a member of our team, we look first and foremost for people who are passionate about solving business problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, as well as partner with stakeholders to stay focused on business goals. We embrace a culture of experimentation and constantly strive for improvement and learning. Youāll work in a collaborative, trusting, thought-provoking environmentāone that encourages diversity of thought and creative solutions that are in the best interests of our customers globally. You'll combine your design and development expertise with a never-ending quest to create innovative technology through solid engineering practices. Youāll work with a highly inspired and inquisitive team of technologists who are developing & delivering top quality technology products to our clients & stakeholders.
Key Responsibilities
- Design and develop state-of-the-art GenAI and general AI solutions as well as multiagent systems to solve complex business problems.
- Integrate knowledge graph, LLMs and multiagent systems
- Leverage NLP techniques to enhance applications in language understanding, generation, and other data-driven tasks.
- Lead the design and architecture of scalable, efficient, and high-performance data systems that support processing of massive datasets of structured and unstructured data.
- Use machine learning frameworks and tools to train, fine-tune, and optimise models. Implement the best practices for model evaluation, validation, and scalability.
- Stay up to date with the latest trends in AI, NLP, LLMs and big data technologies. Contribute to the development and implementation of new techniques that improve performance and innovation.
- Collaborate with cross-functional teams, including engineers, product owners, and other stakeholders to deploy AI models into production systems and deliver value to the business.
- Leverage a strong problem-solving mindset to identify issues, propose solutions, and conduct research to enhance the efficiency of AI and machine learning algorithms.
- Communicate complex model results and actionable insights to stakeholders though compelling visualizations and narratives.
Required Skills and Qualifications
- Masterās or PhD in Computer Science, Mathematics, Engineering, Statistics or a related field
- Proven experience building and deploying to production GenAI models with demonstrable business value realization
- 5+ yearsā experience in traditional AI methodologies including deep learning, supervised and unsupervised learning, and various NLP techniques (e.g, tokenization, named entity recognition, text classification, sentiment analysis etc.)
- Strong proficiency in Python with deep experience using frameworks like Pandas, PySpark, TensorFlow, XGBoost
- Demonstrated experience dealing with big-data technologies and the ability to process, clean and analyse large-scale datasets.
- Experience designing and architecting high-performance, data-intensive systems that are scalable and reliable.
- Strong communication skills to present technical concepts and results to both technical and non-technical stakeholders. Ability to work in a team-oriented and collaborative environment.
- Experience with Prompt Engineering, Retrieval Augmented Generation (RAG), Vector Databases
- Strong understanding of multiagent architectures and experience with frameworks for agent development
- Knowledge of Semantic Knowledge Graphs and their integration into AI/ML workflows
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - arenāt 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, youāll 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. Thereās 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-officesā into your browser.
Expected base pay rates for the role will be between $150,00 and $210,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.
It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.
Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).
Tags: Architecture Big Data Classification Computer Science Data Analytics Data governance Data quality Deep Learning Engineering Finance Generative AI LLMs Machine Learning Mathematics NLP Pandas PhD Prompt engineering PySpark Python RAG Research Statistics TensorFlow Unstructured data Unsupervised Learning XGBoost
Perks/benefits: Career development Gear
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