Senior AI Solutions Engineer VP - P4

Morgan Stanley • New York, NY

17h

About The Position

The Firmwide Data Office (“FDO”) 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 firm’s data architecture and business processes front-to-back, empowering developers by providing consistent means of handling data, facilitate data-driven insights & decision making. 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 Firm’s 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). The “Firmwide Data Office” 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. You’ll work in a collaborative, trusting, thought-provoking environment—one 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. You’ll work with a highly inspired and inquisitive team of technologists who are developing & delivering top quality technology products to our clients & stakeholders.

Requirements

• Master’s 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+ years’ 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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees