Jobs

Engineering-L2-Hyderabad-Associate-Software Engineering
Hyderabad, Telangana, India
·
On-site
·
Full-time
·
6d ago
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., Tensor Flow, Py Torch).
- 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.
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About Goldman Sachs

Goldman Sachs
PublicGoldman Sachs is a multinational investment bank and financial services company providing investment banking, securities, and investment management services. The firm serves corporations, financial institutions, governments, and individuals worldwide.
45,000+
Employees
Lower Manhattan
Headquarters
Reviews
2.6
10 reviews
Work Life Balance
1.8
Compensation
4.2
Culture
2.1
Career
2.9
Management
2.0
25%
Recommend to a Friend
Pros
High compensation and competitive salaries
Talented coworkers and good teamwork
Prestigious work environment
Cons
Poor work-life balance and long hours (70+ weekly)
Toxic and cutthroat competitive culture
High stress and burnout risk
Salary Ranges
21,066 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
6,923 reports
$112,993
total / year
Base
$97,759
Stock
-
Bonus
$15,234
$77,583
$166,892
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
21-35 weeks
Experience
Positive 0%
Neutral 60%
Negative 40%
Interview Process
1
Application Review
2
Phone Screen/HireVue Video Interview
3
Superday/Panel Interview
4
Final Decision
Common Questions
Behavioral/STAR
Technical Knowledge
Culture Fit
Past Experience
Case Study
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