GenAI Platform Solutions Engineer – Associate

Morgan-Stanley

Alpharetta (GA)

On-site

USD 70,000 - 120,000

Full time

14 days+

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Job summary

Morgan Stanley is expanding its AI Development Platform to empower global developers. This role focuses on building GenAI proofs of concept, producing reusable patterns, and documenting best practices to accelerate firmwide AI adoption.

You will work with AI engineers and application owners to deliver prototypes, sample code, and guidance across time zones. The ideal candidate has deep learning expertise, hands-on GenAI experience, and strong communication skills to influence development teams

Qualifications

  • Strong experience building GenAI solutions in production
  • Experience with AI model deployment and lifecycle
  • Ability to document patterns and provide guidance to developers

Responsibilities

  • Build Proof of Concepts and example code to enable GenAI adoption at scale.
  • Develop prototypes to demonstrate model capabilities and usage patterns.
  • Collaborate with AI engineers to prioritize capabilities for the firmwide roadmap.
  • Author best practices on Generative AI tooling, models, and libraries.
  • Troubleshoot customer adoption, update documentation, and feedback to platform teams.
  • This is a customer-facing role requiring strong communication skills.
  • Create reusable code samples for application teams and promote DevOps practices.

Skills

Python
GenAI
Deep learning
TensorFlow
PyTorch
Azure
AWS
GCP
CI/CD
Data governance
Security
Communication
Collaboration

Education

Bachelor's degree in Computer Science
Master's degree in Computer Science

Tools

GitHub
Bitbucket

Job description

Morgan Stanley is expanding its AI Development Platform to empower global developers. This role focuses on building GenAI proofs of concept, producing reusable patterns, and documenting best practices to accelerate firmwide AI adoption.

You will work with AI engineers and application owners to deliver prototypes, sample code, and guidance across time zones. The ideal candidate has deep learning expertise, hands-on GenAI experience, and strong communication skills to influence development teams

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