Overview
On Site
Full Time
Skills
Agile
Startups
Prototyping
Pivotal
Ideation
Rapid Prototyping
Partnership
Solution Architecture
Use Cases
Specification Gathering
Workflow
Knowledge Transfer
Documentation
Training
Pair Programming
Leadership
Innovation
Computer Science
Data Science
Prompt Engineering
Programming Languages
Python
Artificial Intelligence
Machine Learning (ML)
TensorFlow
PyTorch
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud
Google Cloud Platform
Machine Learning Operations (ML Ops)
Management
Communication
Articulate
Collaboration
Mentorship
Job Details
Job Description
Summary
The agile AI Innovation Acceleration team will operate with the speed and spirit of a startup, focused on rapidly prototyping and building cutting-edge AI use cases that directly address the critical needs of our businesses. The primary goal of this team is to demonstrate the transformative potential of AI within the firm, rapidly deliver impactful solutions, and then seamlessly transfer the code, knowledge, and ownership to the respective business and engineering teams. This hands-on engineering role is pivotal in shaping the future of AI adoption at Goldman Sachs and fostering a culture of innovation and accelerated development.
As an AI Innovation Acceleration Specialist, you will be instrumental in identifying, developing, and deploying end-to-end AI/Machine Learning solutions that drive tangible business value; you will work in a fast-paced environment, leveraging your expertise to translate complex business challenges and customer needs into actionable AI architectures and technical specifications, and then implement and deliver these systems.
Key Responsibilities
Rapid Prototyping & End-to-End Development: Lead the end-to-end development of AI/ML models and applications, from ideation and data exploration to rapid prototyping and initial deployment.
Business Partnership & Solution Architecture: Collaborate closely with business and engineering teams to deeply understand their challenges and customer needs, identify high-impact AI use cases, and translate business requirements into robust technical specifications and solution architectures.
Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable AI solutions based on defined technical specifications and architectures, ensuring seamless integration with existing systems and workflows within the Goldman Sachs ecosystem.
Knowledge Transfer & Enablement: Facilitate effective knowledge transfer through comprehensive documentation, training sessions, mentorship, and pair-programming, empowering receiving teams to take ownership and continue the development of AI solutions.
Technology & Innovation Leadership: Stay abreast of the latest advancements in AI, machine learning, and relevant technologies, continuously evaluating and recommending new tools, techniques, and best practices to drive innovation.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field.
5+ years of hands-on experience in AI/ML development, with a proven track record of delivering end-to-end AI solutions in a professional setting.
Demonstrated experience building and deploying end-to-end AI applications, particularly those leveraging LLMs and related frameworks. This includes experience with prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and agentic frameworks.
Strong proficiency in programming languages such as Python, along with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch).
Proven ability to translate complex business requirements and customer needs into well-defined technical architectures and specifications, and to subsequently implement and deliver robust systems based on these designs.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and MLOps practices for model deployment and management.
Excellent communication capabilities, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders across all levels of the organization.
Strong collaboration and interpersonal skills, with a passion for mentoring and enabling others.
Proven ability to lead or significantly contribute to cross-functional projects.
Summary
The agile AI Innovation Acceleration team will operate with the speed and spirit of a startup, focused on rapidly prototyping and building cutting-edge AI use cases that directly address the critical needs of our businesses. The primary goal of this team is to demonstrate the transformative potential of AI within the firm, rapidly deliver impactful solutions, and then seamlessly transfer the code, knowledge, and ownership to the respective business and engineering teams. This hands-on engineering role is pivotal in shaping the future of AI adoption at Goldman Sachs and fostering a culture of innovation and accelerated development.
As an AI Innovation Acceleration Specialist, you will be instrumental in identifying, developing, and deploying end-to-end AI/Machine Learning solutions that drive tangible business value; you will work in a fast-paced environment, leveraging your expertise to translate complex business challenges and customer needs into actionable AI architectures and technical specifications, and then implement and deliver these systems.
Key Responsibilities
Rapid Prototyping & End-to-End Development: Lead the end-to-end development of AI/ML models and applications, from ideation and data exploration to rapid prototyping and initial deployment.
Business Partnership & Solution Architecture: Collaborate closely with business and engineering teams to deeply understand their challenges and customer needs, identify high-impact AI use cases, and translate business requirements into robust technical specifications and solution architectures.
Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable AI solutions based on defined technical specifications and architectures, ensuring seamless integration with existing systems and workflows within the Goldman Sachs ecosystem.
Knowledge Transfer & Enablement: Facilitate effective knowledge transfer through comprehensive documentation, training sessions, mentorship, and pair-programming, empowering receiving teams to take ownership and continue the development of AI solutions.
Technology & Innovation Leadership: Stay abreast of the latest advancements in AI, machine learning, and relevant technologies, continuously evaluating and recommending new tools, techniques, and best practices to drive innovation.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field.
5+ years of hands-on experience in AI/ML development, with a proven track record of delivering end-to-end AI solutions in a professional setting.
Demonstrated experience building and deploying end-to-end AI applications, particularly those leveraging LLMs and related frameworks. This includes experience with prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and agentic frameworks.
Strong proficiency in programming languages such as Python, along with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch).
Proven ability to translate complex business requirements and customer needs into well-defined technical architectures and specifications, and to subsequently implement and deliver robust systems based on these designs.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and MLOps practices for model deployment and management.
Excellent communication capabilities, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders across all levels of the organization.
Strong collaboration and interpersonal skills, with a passion for mentoring and enabling others.
Proven ability to lead or significantly contribute to cross-functional projects.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.