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

Help turn cutting edge AI research into real, production grade capabilities used across the firm. You will build secure, scalable platforms and applications that accelerate experimentation while meeting high engineering standards. You will partner closely with AI Researchers and Data Scientists to move prototypes into optimized, reliable solutions. You will grow your influence by mentoring others and helping shape team practices. You will join a team that values collaboration, inclusion, and continuous improvement.

As a Software Engineer III in AI and Machine Learning Data Platforms, you will deliver critical technology solutions that support the firm’s business objectives. You will work directly with AI Research and the Machine Learning Center of Excellence to advance experiments into robust, scalable applications. You will build platform and application capabilities, including generative AI solutions, with a focus on security, stability, and operational excellence. You will contribute to an engineering culture that values strong delivery practices, mentorship, and inclusive teamwork.

Job Responsibilities

Collaborate with Data Scientists and AI Researchers to advance experiments into scalable, optimized, production grade applications

Develop software applications for AI and machine learning platforms, including generative AI applications such as agents

Design and troubleshoot technical solutions using creative problem solving to address complex engineering challenges

Identify and automate remediation for recurring issues and developer pain points to improve operational efficiency

Deliver solutions using continuous integration and continuous delivery pipelines to public and private cloud platforms

Support experimentation environments, including tools such as Jupyter Notebooks

Mentor junior engineers and help drive engineering practices across the team and with research partners

Contribute to a team culture of diversity, opportunity, inclusion, and respect

Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required Qualifications, Capabilities, and Skills

Formal training or certification in software engineering concepts with applied full stack development experience

Practical experience developing infrastructure as code, ideally using Terraform

Hands-on experience building applications, testing, and supporting operational stability

Proficiency in at least one programming language, with a strong focus on Python

Experience with automation and continuous integration, delivery, and testing methods

Working knowledge of the Software Development Life Cycle and Model Development Life Cycle

Understanding of agile methodologies and basic proficiency with architectural frameworks

Demonstrated experience in platform development within a technical discipline such as cloud, artificial intelligence, or machine learning

Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.

Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred Qualifications, Capabilities, and Skills

Experience using AI tools to improve productivity and efficiency in daily work

Proactive approach to identifying issues and challenging the status quo constructively

Initiative in learning and adapting to new technologies and methodologies

Experience or exposure to business facing integrated application environments such as risk or trading

Strong problem solving skills with a focus on innovation and continuous improvement

Strong communication and collaboration skills across cross functional teams