Hiring.Camp

Software Engineer

Ms

·

Apr 23, 2026

Salary
$165k+
Location
750 Seventh Ave- NY, United States of America
Type
Full-time
Department
Engineering
Education
Master
Source
Workday

Description

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 Engineering position at the Director level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.


Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.


Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on.


We are seeking a skilled GenAI Engineer to join our technology team. In this role, you will be responsible for taking AI/ML proof-of-concepts and experiments and scaling them into secure, resilient, and compliant production solutions. You will work closely with data engineers, product managers, and domain experts to develop GenAI-powered solutions for our investment banking and capital markets businesses.


What you’ll do in the role:

  • Work collaboratively with software engineers and stakeholders to productize GenAI prototypes, ensuring scalability, robustness, and maintainability in a regulated environment.

  • Design, implement, and optimize LLM, RAG, or Agentic workflows and GenAI pipelines using Python, Langgraph, or other relevant frameworks.

  • Integrate GenAI solutions with complex Investment Banking and Capital Market workflows.

  • Ensure GenAI models and applications comply with relevant regulations (e.g., GDPR, SEC) and internal governance.

  • Optimize inference speed, resource utilization, and orchestration of GenAI models for production workloads.

  • Monitor and troubleshoot production GenAI services, driving continuous improvement.

  • Collaborate cross-functionally with technology, product, and domain teams to gather requirements, prioritize features, and deliver end-to-end solutions.

  • Document architectural and technical decisions; train and support other teams as needed. 

What you’ll bring to the role:

  • Bachelor's or Master's in Computer Science, Engineering, Mathematics, or a related field.

  • 5+ years of hands-on experience building and deploying ML/AI applications into production at scale.

  • Demonstrated expertise in Generative AI technologies (e.g., LLMs, transformers, prompt engineering, RAG, Agent, fine-tuning).

  • Strong programming skills in Python and one or more ML/Deep Learning frameworks (PyTorch,etc.).

  • Experience with MLOps frameworks (Kubeflow, MLflow, Airflow) and productionizing AI applications.

  • Deep understanding of cloud infrastructure (AWS, Azure, GCP) and containerization (Docker, Kubernetes).

  • Prior exposure or experience working in investment banking, capital markets, or regulated financial environments.

  • Experience integrating ML/AI solutions with enterprise systems and APIs Strong problem-solving, communication, and documentation skills.

Nice to Haves:

  • Experience with data privacy, anonymization, and AI model governance in financial institutions.

  • Exposure to knowledge graphs, or hybrid AI architectures. Certifications in cloud technologies or ML (e.g., AWS Certified ML Engineer, Azure AI Engineer).

This role offers the opportunity to:
Work in an open environment where everyone can express their views and make significant contributions.

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.

Expected base pay rates for the role will be between $120,000 and $165,000 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 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.

Skills

PythonAWSAzureGCPDockerKubernetesDeep LearningPyTorchAirflowGDPRAWS Certified

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Software Engineer at Ms • $165k+ | Hiring.Camp