AI Development Solution Engineer - Associate

AI Development Solution Engineering Specialist

Job Description Our mission is to develop a firmwide Artificial Intelligence (AI) Development Platform that aligns with the firm's Technology principles and drives efficiency and consistency, controls, security and strong governance and promotes innovation, enabling teams to build applications that leverage AI capabilities and accelerate the adoption of AI across our businesses.

This role is for a solution engineering specialist to work with GenAI application owners to adopt GenAI platform capabilities and develop patterns and best practices to enable GenAI application adoption  ideal candidate will have strong knowledge and experience on deep learning, contemporary model architectures and a strong drive to solve real-world problems with AI techniques. They will have hands-on experience developing GenAI applications and can leverage their expertise to enable firmwide developers to adopt AI techniques at scale through documentation, consultation, and collaborative Proof of Concept and sample code  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.

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: Build Proof of Concepts and example code through which developers can leverage GenAI models to solve common problems or patterns to enable GenAI adoption at scale Develop prototypes to demonstrate model capabilities, advanced usage patterns. Collaborate with AI engineers to prioritize capabilities for firmwide platform roadmap Author best practices on the Generative AI ecosystem, when to use which tools, available models such as GPT, Llama, Hugging Face etc.

and libraries such as Langchain, and Sematic Kernel. Troubleshoot customer adoption of genAI platform capabilities; update user documentation and provide feedback to platform engineering teams to improve future customer experience This is a customer-facing role and excellent soft communications skills are mandatory. Have an application developer mindset and build common, reusable solutions to scale Generative AI use cases using pre-trained models as well as fine-tuned models.

What you'll bring to the role: Bachelor's or a master's degree in computer science or 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 specific libraries like numpy, opencv, scikit-learn, pandas, matplotlib, seaborn, etc. Understanding of AI/ML Lifecycle and basic understanding of systems like mlflow, Dataiku, databricks.

Broad understanding of data engineering (SQL, No

SQL, Big Data), data governance, data privacy and security Demonstrated experience in Dev Ops, understanding of CI/ CD. Hands on experience with managing code in code repositories such as Bit Bucket and Git Hub. Understanding of how deep learning works, understanding of Machine Learning frameworks such as Tensor Flow or PyTorch Ability to articulate technical concepts effectively to diverse audiences. Excellent communication skills.

Strong desire and ability to influence development teams and help them adopt AI. Demonstrated ability to work effectively and collaboratively in a global organization, across time zones, and across organizations

Nice to have Experience working with application development teams to enable them to build AI based applications. Ability to create code samples to be shared with application teams. Experience working with cloud providers, preferably Azure, but also AWS, GCP Experience building applications using AI development services on prominent cloud platforms such as Azure Open AI, Azure AI Foundry, Azure Search, Azure Cognitive Services, AWS Bedrock, AWS Sagemaker, Google Vertex AI Experience working in a large, regulated industry such as Financial Services, Insurance etc.

Experience building AI applications, preferably Generative AI and LLM based apps. Experience working with Generative AI development, embeddings, fine tuning of Generative AI models. Understanding of Model Ops/ ML Ops/ LLM Ops What you can expect from Morgan Stanley:

We have a track record of…