Engineering-L2-Hyderabad-Associate-Software Engineering

Summary

The Document AI Platform team is focused on 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, especially as it relates to exciting information from documents. 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 Document AI engineer, 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

• Vendor Replacement & Re-Imagining Ops Workflows: Using generative AI, re-imagine operations workflows focused on manually extracting data from documents, including but not limited to migrating off vendor products used for data extraction from documents. 
• 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.
• 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 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, GCP) 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.

About Goldman Sachs

The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.