AI Cloud Solution Engineering Specialist developing generative AI solutions at Morgan Stanley in Montreal. Collaborating with teams to enhance cloud services and improve developer experience.
Responsibilities
Build POC’s and example code through which developers can access Gen AI models via standard APIs.
Collaborate with other engineers and teams to onboard new cloud services to Morgan Stanley
Architect new cloud solutions for new use cases consistent with Morgan Stanley security standards.
Have an application developer mindset and build common, reusable solutions to scale generative AI use cases.
Contribute to major design decisions and product selection for building generative AI solutions.
Develop tooling and self-service capabilities for deploying AI solutions.
Collaborate with developers to enhance the developer’s experience when building and deploying AI applications.
Document best practices on generative AI ecosystems, when to use which tools, available models such as GPT, Llama, Claude, etc. and libraries such as Langchain and Sematic Kernel.
Requirements
At least 4+ years of experience in enterprise software engineering, design, and development
At least 4+ years of experience implementing enterprise architecture in at least one major cloud provider (Azure, AWS, GCP).
Bachelor's or a master's degree in computer science or related field, or equivalent job experience.
Strong hands-on development background in Python (specifically API based development in Flask or FastAPI), additional languages are a bonus.
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 building AI applications, preferably Generative AI and LLM based apps.
Experience deploying resources to the cloud via terraform and CI/CD pipelines
Experience designing and implementing highly scalable architecture for enterprise applications
Ability to create code samples for baseline implementations.
Demonstrated experience in DevOps, understanding of CI/ CD.
Hands on experience with managing code in code repositories such as Bit Bucket and GitHub.
Broad understanding of data engineering (SQL, NoSQL, Big Data), data governance, data privacy and security
Ability to articulate technical concepts effectively to diverse audiences.
Strong desire and ability to influence development teams and help them adopt AI.
Demonstrated ability to work effectively in a global organization and across time zones.
Understanding of information security and secure coding practices.
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