The AI Application Engineer will work within the Core Engineering Shared Services AI team, focusing on developing and implementing AI solutions that enhance business processes. This role involves collaborating with internal business and engineering partners to transform complex operational challenges into effective AI products. The engineer will lead the design and deployment of cloud-native applications while ensuring they are secure and reliable. The position emphasizes rapid prototyping, production AI architecture, and the transition of solutions to operational teams.

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field.
• 9+ years of hands-on software engineering experience building, deploying, and supporting robust production applications.
• Strong proficiency in Python, Java, or Go, with demonstrated ability to apply sound software engineering, testing, data modeling, and system design practices.
• Proven experience translating complex business requirements into cloud-optimized application architectures, scalable data models, and technical specifications for production delivery.
• Experience operating in a forward-deployed or internal client-facing engineering model, including workflow discovery and stakeholder engagement.
• Extensive experience with major cloud platforms such as AWS, Azure, or GCP, including serverless and containerization.
• Experience designing cloud-based AI solution architectures that integrate managed AI services and secure data access.
• Demonstrated experience integrating LLM or AI/ML capabilities into production applications.
• Excellent communication and collaboration skills, with the ability to engage technical and non-technical stakeholders.

• Lead the design, build, deployment, and operationalization of cloud-native AI applications.
• Partner with business and engineering teams to identify high-impact AI opportunities and translate requirements into cloud-optimized architectures.
• Embed with The Core business teams to map workflows and identify pain points for automation.
• Build AI applications using LLM APIs and other advanced technologies for production use.
• Apply cloud-native services and MLOps practices to ensure applications are scalable and resilient.
• Document solutions and mentor receiving teams for a smooth transition of application code and operational practices.

• Employees at Goldman Sachs are often offered comprehensive benefits, including medical, dental, life and disability coverage, generous vacation and holidays, and robust wellness resources such as EAP counseling, medical advocacy, on-site/virtual health services, and fitness support. Financial perks typically include retirement savings programs, live financial education, education support, and wealth-creation opportunities through equity awards and select investment programs. Many locations also provide family benefits (childcare resources, parental and family leaves, adoption/surrogacy support) and flexible work options like part-time schedules, job sharing, telecommuting, and alternate hours.