AI Development Solution Engineer - Associate
About The Position
Morgan Stanley is developing a firmwide Artificial Intelligence (AI) Development Platform aligned with the firm's Technology principles. The platform is intended to drive efficiency and consistency, strengthen controls, security, and governance, promote innovation, and help teams build applications that use AI capabilities and accelerate AI adoption across the business. The AI Development Solution Engineer works with Generative AI (GenAI) application owners to adopt platform capabilities and develops patterns and best practices that support adoption at scale. This customer-facing role requires hands-on experience developing GenAI applications, knowledge of deep learning and contemporary model architectures, and the ability to solve practical problems using AI. The specialist helps firmwide developers adopt AI techniques through documentation, consultation, collaborative proofs of concept, prototypes, and sample code.
Requirements
- Bachelor's or master's degree in computer science or a related field, or equivalent job experience.
- 8–12 years of experience in software engineering, design, and development.
- Experience developing GenAI applications.
- Strong hands-on proficiency in Python and machine-learning libraries such as NumPy, OpenCV, scikit-learn, pandas, matplotlib, and seaborn.
- Understanding of the AI/ML lifecycle and basic familiarity with systems such as MLflow, Dataiku, and Databricks.
- Broad understanding of data engineering, including SQL, NoSQL, and big data, as well as data governance, privacy, and security.
- Demonstrated DevOps experience and understanding of CI/CD.
- Hands-on experience managing code in repositories such as Bitbucket and GitHub.
- Understanding of deep learning and machine-learning frameworks such as TensorFlow or PyTorch.
- Excellent communication skills and ability to articulate technical concepts to diverse audiences.
- Strong desire and ability to influence development teams and help them adopt AI.
- Ability to work collaboratively and effectively across organizations and time zones in a global organization.
Nice To Haves
- Experience working with application development teams to enable them to build AI-based applications.
- Ability to create code samples for application teams.
- Experience with cloud providers, preferably Azure, as well as AWS or GCP.
- Experience building applications with AI development services on cloud platforms, such as Azure OpenAI, Azure AI Foundry, Azure Search, Azure Cognitive Services, AWS Bedrock, AWS SageMaker, or Google Vertex AI.
- Experience working in a large, regulated industry such as financial services or insurance.
- Experience building AI applications, preferably Generative AI and LLM-based applications.
- Experience with Generative AI development, embeddings, and fine-tuning Generative AI models.
- Understanding of ModelOps, MLOps, or LLMOps.
Responsibilities
- Build proofs of concept and example code that show developers how to use GenAI models to solve common problems and patterns, enabling adoption at scale.
- Develop prototypes that demonstrate model capabilities and advanced usage patterns.
- Collaborate with AI engineers to prioritize capabilities for the firmwide platform roadmap.
- Author best practices for the Generative AI ecosystem, including guidance on tools, models such as GPT, Llama, and Hugging Face, and libraries such as LangChain and Semantic Kernel.
- Troubleshoot customer adoption of GenAI platform capabilities, update user documentation, and provide feedback to platform engineering teams to improve the customer experience.
- Develop common, reusable solutions that help scale Generative AI use cases with pre-trained and fine-tuned models.
- Communicate technical concepts effectively to diverse audiences and influence development teams to adopt AI.
Benefits
- Comprehensive employee benefits and perks
- Employee benefits and support for employees and their families throughout their work-life journey
- Opportunities to move about the business
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What This Job Offers
Job Type
Full-time
Career Level
Senior
