ABOUT MORGAN STANLEY
Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, wealth management and investment management services. With offices in more than 41 countries, the Firm's employees serve clients worldwide including corporations, governments, institutions, and individuals. For further information about Morgan Stanley, please visit www.morganstanley.com.
ABOUT PARAMETRIC
Parametric is part of Morgan Stanley Investment Management, the asset management division of Morgan Stanley. We partner with advisors, institutions, and consultants to build portfolios focused on what's important to them and their clients. A leader in custom solutions for more than 30 years, we help investors access efficient market exposures, solve implementation challenges, and design multi-asset portfolios that respond to their evolving needs. We also offer systematic alpha and alternative strategies to complement clients' core holdings.
This role is part of Parametric's hybrid working model, which includes working in the office 3 days a week and choosing to work remotely or in the office the remaining days of the week.
ABOUT THE TEAM
The Core Platform and AI Engineering team at Parametric is responsible for enhancing the quality and velocity of engineering outcomes across the technology organization through platform-level capabilities, accelerating engineering teams and enabling them to focus on delivering business value.
This team delivers Parametric's platform-level service and development capabilities. These efforts seek to optimize the organization's technology posture by providing common solutions to shared problems which drive standardization, accelerated delivery, reduced risk and cost, and scalable, high-performing results. The team serves engineering teams across the organization and is responsible for supporting their success.
ABOUT THE ROLE
The Senior Software Engineer (Generative AI) will serve as a core technical enabler across business units, applying deep knowledge of ML, NLP, transformers, and LLMs to design, evaluate, and operationalize generative AI solutions.
This role bridges business stakeholders and engineering teams, translating business problems into technical solutions grounded in data availability and feasibility while enabling engineering teams to fully utilize the advanced AI capabilities available at Morgan Stanley. Through expertise in the AI development lifecycle, from problem framing through evaluation and regression testing, combined with a platform mindset, this role ensures Parametric's GenAI solutions are robust, measurable, and continuously improving.
Parametric values strong software engineering and takes pride in their culture of technical rigor, modern practices, and continuous growth. This role will help translate that culture into practical platform solutions which promote engineering effectiveness and consistent delivery.
PRIMARY RESPONSIBILITES
- Translate business problems into technical solutions by assessing data availability, feasibility, and alignment with GenAI capabilities.
- Own and drive the AI development lifecycle end-to-end: problem scoping, data assessment, solution design, implementation, evaluation, deployment, and iteration.
- Design and execute AI system evaluation frameworks, including quantitative metrics definition, discriminative testing (e.g., A/B, sensitivity analysis), regression testing, and continuous quality monitoring of GenAI outputs.
- Apply deep knowledge of ML, NLP, Transformer architectures, and LLM internals (tokenization, attention, decoding strategies, fine-tuning paradigms) to select, adapt, and optimize foundation models (OpenAI, Llama, open source, etc.) for diverse use cases.
- Design, develop, and maintain platform-level GenAI applications leveraging prompt engineering, RAG pipelines, fine-tuning, and agentic workflows to drive business outcomes.
- Interact directly with business users and engineering teams to understand requirements, scope solutions, and communicate technical trade-offs in accessible terms.
- Conduct code and design reviews for developers working on generative AI solutions, ensuring adherence to engineering best practices and evaluation standards.
- Implement and manage cloud deployments using AWS service, ensuring high availability, scalability, and observability.
- Maintain and enhance existing AI applications to improve model performance, reliability, and user experience through data-driven iteration.
JOB QUALIFICATIONS
- Required Experience: 7+ years
Skill set: Python, REST APIs, LLM APIs / OpenAI, Prompt Engineering, AWS
Primary Skills- Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field of study.
- 5+ years of hands-on Python software design and development.
- Strong communication skills, with the ability to effectively convey technical concepts to both business users and technical audiences alike.
- Strong conceptual and practical understanding of ML, NLP, Transformers, and LLMs, including model architectures, training/fine-tuning paradigms, evaluation methodologies, and common failure modes.
- Demonstrated experience with the AI development lifecycle: problem framing, data assessment, model selection, prompt engineering, evaluation metrics design, testing (discriminative, regression, bias), and deployment.
- Experience translating business problems into technical requirements, with the ability to assess data readiness and scope feasible AI solutions.
- Proficiency with LLM APIs (OpenAI, Azure OpenAI, Anthropic, open-source model serving) and frameworks (LangChain, LlamaIndex, or equivalent).
- Hands-on experience building cloud-based solutions, preferably on AWS.
- Familiarity with ML/DL frameworks: PyTorch, TensorFlow, or Hugging Face Transformers.
- Familiarity with microservices architecture, containerization (Docker), and REST API design.
- Working experience with Agile development and Git version control.
- Knowledge of RAG architectures, vector databases, and retrieval-augmented workflows.
Good to Have Skills- Financial services industry experience.
- Cloud-native development experience (AWS preferred).
- Experience deploying resources using IaC technologies such as Terraform.
- Experience developing CI/CD pipelines using tools like GitLab CI or GitHub Actions.
- Familiarity with observability and monitoring of AI systems in production (e.g., Datadog).
- Experience building evaluation and benchmarking frameworks for GenAI outputs (golden sets, human-in-the-loop review, automated scoring).
- Experience presenting technical contributions and innovations to technical colleagues.
Parametric believes each member of our organization makes a significant contribution to our success. That contribution should not be limited by the assigned responsibilities. Therefore, this job description is designed to outline primary duties and qualifications. It is our expectation that every member of our team will offer his/her/their services wherever and whenever necessary to ensure the success of our client services.
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 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 .
