GenAI Search and Document Management Vice President – Goldman Sachs, Toronto, ON
Location: Toronto, ON | Company: Goldman Sachs
Goldman Sachs is hiring a GenAI Search and Document Management Vice President in Toronto, Ontario, to help develop artificial intelligence platforms supporting document digitization, information retrieval and financial services workflows.
This senior software engineering position sits within the Engineering Division and focuses on production-ready Generative AI systems. The successful candidate will contribute to Retrieval-Augmented Generation pipelines, knowledge graphs, cloud-native services and internal AI tools designed to help employees access and use complex business information more effectively.
Engineering Generative AI for Financial Services
The role supports Goldman Sachs’ broader effort to apply Generative AI to proprietary research, analytics and financial data. Rather than focusing only on experimental models, the position involves turning AI concepts into dependable software that can operate within a highly regulated and technically demanding financial environment.
The Vice President will work with engineers, researchers and business stakeholders to understand practical document-management challenges and design systems that improve search, knowledge access and developer productivity. Projects may involve large language models, document-processing workflows, structured knowledge representations and services that connect employees with relevant internal information.
Key Areas of Responsibility
The position combines applied artificial intelligence, software engineering and technical leadership. Responsibilities extend from early experimentation and architecture decisions through testing, deployment and ongoing production support.
Document Digitization
Help build an AI-enabled platform that can process, organize and retrieve information from complex documents used across financial and business operations.
Generative AI Development
Design and evaluate AI-based software systems that use modern language models and information-retrieval techniques to address practical business requirements.
RAG and Knowledge Graphs
Develop Retrieval-Augmented Generation pipelines and knowledge-graph capabilities that improve the relevance, traceability and usefulness of generated responses.
Production Engineering
Write, test and maintain reliable code that meets the quality, performance and operational expectations of a global financial services organization.
Cloud-Native Services
Develop and deploy scalable services within cloud-based environments while considering security, resilience, monitoring and long-term maintainability.
Technical Leadership
Lead initiatives that involve multiple teams, establish technical direction and help colleagues move complex AI projects from concept into production.
Education and Professional Experience
Goldman Sachs is seeking candidates with a master’s degree or Ph.D. in computer science, machine learning, mathematics, statistics, physics, engineering, quantitative finance or a comparable discipline. Equivalent industry experience may also be considered when it demonstrates the required technical depth.
Applicants should have at least five years of relevant professional experience and a strong background in software development for quantitative investment workflows. Experience supporting equities, fixed income or multi-asset strategies is particularly relevant because the role applies advanced engineering and AI methods within financial markets and investment-related environments.
Skills That May Help Candidates Succeed
This position requires more than familiarity with AI models. Successful candidates will need to combine technical depth, software engineering discipline and the ability to collaborate with business and engineering teams across a large organization.
Experience with large language models, RAG architectures, document intelligence or related AI systems can support the development of practical internal tools.
Proficiency in contemporary programming languages such as Python, C++ or Java is needed to build reliable services and production-quality applications.
Understanding investment workflows and financial markets helps ensure that technical solutions reflect the needs of analysts, engineers and business users.
The ability to design scalable, maintainable and secure platforms is important when AI systems must support enterprise-level data and document workloads.
Clear communication and sound technical judgment help the Vice President coordinate projects involving engineers, researchers and business stakeholders.
Working Within the Engineering Division
This Toronto-based opportunity belongs to Goldman Sachs’ Engineering Division, where technology teams develop platforms supporting markets, investment activities, risk management and internal business operations. The work requires close cooperation between technical specialists and professionals who use these systems in demanding financial environments.
The official posting displays a salary value of “CAD 1,” which appears incomplete and has therefore not been treated as a reliable compensation range. Candidates should consult the employer’s application page for current compensation information, employment conditions and any benefits that may apply to the position.
How to Apply
Candidates should review the complete position on Goldman Sachs’ official careers platform before applying. The employer’s page contains the most current information regarding qualifications, responsibilities, workplace expectations and the recruitment process.
Applicants should prepare a résumé that clearly explains their Generative AI experience, production software engineering background, programming skills and work with quantitative investment systems. Relevant examples involving document intelligence, RAG pipelines, knowledge graphs or cloud-native AI services should be highlighted where applicable.