Software Engineer III – AI/ML Data Platforms – AI Engineer – Python

Overview

You will transform cutting-edge AI research into production-grade capabilities at a leading financial firm. In this role, you collaborate with AI researchers and data scientists to move prototypes into reliable, scalable solutions while upholding strong engineering standards. You’ll build platform and application capabilities, including generative AI features, with emphasis on security, stability, and operational excellence. You contribute to an engineering culture that values mentorship, diversity, and continuous improvement, and you will shape practices across teams and partners.

Responsibilities

• Collaborate with Data Scientists and AI Researchers to turn experiments into scalable, production-grade applications
• Develop software for AI/ML platforms including generative AI agents
• Design and troubleshoot solutions with creative problem solving for complex engineering challenges
• Automate recurring issues to improve operational efficiency
• Deliver solutions via CI/CD pipelines to cloud platforms
• Support experimentation environments (e.g., Jupyter Notebooks)
• Mentor junior engineers and promote engineering practices
• Foster a culture of diversity, inclusion, and respect
• Leverage enterprise AI coding assist tools to improve code quality and productivity, with peer review and secure coding standards
• Apply SDLC/Model Development Life Cycle knowledge to enhance automation and value

Key requirements

• Formal training or certification in software engineering with full stack development experience
• Practical experience with infrastructure as code (Terraform)
• Hands-on application development, testing, and operational stability support
• Proficiency in Python
• Experience with automation, CI/CD, and testing methods
• Working knowledge of SDLC and Model Development Life Cycle
• Understanding of agile methodologies and architectural frameworks
• Experience in platform development within cloud/AI/ML
• Hands-on use of enterprise AI-assisted development tools with ability to validate AI outputs for correctness, performance, and security
• Understanding of responsible AI use, data sensitivity, secure handling of inputs/outputs, and adherence to security and resiliency expectations

• Strong collaboration and cross-functional communication
• Mentorship and leadership willingness
• Proactive problem solving and questioning status quo
• Python
• Terraform
• CI/CD

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