Job Description

Profile

We’re seeking someone to join our Enterprise Technology team as a Software Engineer - AI, Data & Agentic Systems, in Enterprise Network Services with strong hands-on experience in Python and SQL, and a passion for building AI powered, data driven systems. This role sits at the intersection of applied AI, data engineering, and agentic systems, with a focus on delivering production grade, scalable solutions. The ideal candidate is an engineer who understands that AI delivers value only when paired with reliable data pipelines, robust software design, and operational excellence. Experience with Agentic AI systems, including Model Context Protocol (MCP) based architectures, is highly desirable.

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 Director position that develops and maintains 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:

• Design, develop, and operate end to end AI enabled applications using Python.
• Build scalable backend services that integrate machine learning and agentic AI workflows
• Develop and maintain batch and streaming data pipelines supporting analytics, AI training, and inference
• Implement AI agents that reason, plan, and act across tools and data sources using MCP based patterns
• Write efficient and optimized SQL for data transformation, analytics, and feature generation
• Collaborate with data scientists, product managers, and partner engineering teams
• Apply engineering best practices including testing, monitoring, logging, and secure coding
• Participate in design reviews and contribute to system architecture decisions
• Ensure AI systems are responsible, observable, and reliable in production
• Clearly document designs, trade-offs, and operational considerations"

What you’ll bring to the role:

• At least 4+ years' relevant experience would generally be expected to find the skills required for this role
• Bachelor’s degree in computer science, Engineering, Mathematics, or a related technical field or equivalent practical experience.
• 4+years of professional software development experience
• Strong hands-on experience with Python
• Strong proficiency in SQL, including complex queries, joins, and performance tuning
• Solid understanding of data structures, algorithms, and object-oriented design
• Experience building or consuming RESTful APIs
• Experience with version control systems and collaborative workflows (Git)

AI & Intelligent Systems:

• Strong understanding of AI and machine learning fundamentals
• Experience building or integrating ML models into applications
• Familiarity with ML frameworks and libraries (e.g., PyTorch, TensorFlow, scikit learn)
• Understanding of the ML lifecycle: data preparation, training, evaluation, deployment, and monitoring
• Experience or strong interest in Agentic AI systems, including:
• Multi step reasoning and planning, Tool calling and orchestration, Context management and memory
• Exposure to Model Context Protocol (MCP) for building extensible, tool aware AI agents ?

Data Engineering & Streaming Skills:

• Experience working with structured and semi structured data
• Understanding of batch and streaming data processing concepts
• Ability to design data pipelines that support AI, analytics, and operational workloads
• Strong focus on data quality, reliability, and performance
• Experience with Snowflake , Singlestore ,MongoDB, Databricks

Preferred Skills:

• Hands on experience with Kafka, FluentBit, Apache NiFi, or similar data ingestion tools
• Experience with stream processing frameworks (Kafka Streams)
• Exposure to cloud platforms
• Experience with containerized and microservices architectures
• Familiarity with deploying and operating AI agents in production
• Understanding of observability, monitoring, and performance tuning for data intensive systems"

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.

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.