Engineering Division - GenAI and DocAI Engineering - Associate - Hyderabad
Goldman Sachs · Hyderabad · 5+ yrs experience · Posted 2026-06-03
Tech stack: AWS, Azure, GCP, Python
About the role
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.
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
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, 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.
- Proven ability to lead or significantly contribute to cross-functional projects.
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, 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.
- Proven ability to lead or significantly contribute to cross-functional projects.
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