Software Engineer, Global Investment Research, Agentic Systems - Associate

Goldman Sachs • Dallas, TX

6h

About The Position

Goldman Sachs Global Investment Research (GIR) is seeking an Agentic Systems Engineer to build, enhance, and productionize intelligent research tools and automated agentic pipelines. The role collaborates with senior engineers to develop end-to-end full-stack applications, implement advanced retrieval-augmented generation (RAG) components, and integrate AI services into mission-critical GIR platforms.

The engineer builds analyst-facing frontend features and backend APIs and microservices, implements agentic workflows and evaluation pipelines, and deploys AI components using AWS enterprise services. The role also supports production operations, applies disciplined software development practices, and collaborates with business stakeholders and cross-functional teams in Agile sprints.

Goldman Sachs describes its engineering work as building scalable software and systems, architecting low-latency infrastructure, guarding against cyber threats, and using machine learning and financial engineering to turn data into action. The company also describes Engineering as central to its AI-driven business.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.
• 3–5 years of hands-on software engineering experience.
• Proficiency in Java or Python and modern full-stack web technologies such as React, TypeScript, FastAPI, or Spring Boot.
• Practical experience building generative AI applications using Google ADK, LangGraph, or equivalent agentic frameworks, vector databases, and AWS Bedrock.
• Experience implementing evaluation pipelines and prompt testing using Braintrust, AgentCore Eval, equivalent technologies, or custom benchmark harnesses.
• Working knowledge of AWS Lambda, ECS/Fargate, S3, EventBridge, CloudWatch, and API Gateway.
• Solid understanding of SDLC tooling, automated testing, Git, Docker, and CI/CD automation.

Nice To Haves

• Exposure to financial domain data, investment research workflows, or enterprise content authoring tools.
• Practical understanding of token optimization, prompt caching, and latency reduction strategies.
• Familiarity with guardrail frameworks that defend against prompt injection and unauthorized data access.
• Experience building asynchronous or event-driven microservices across polyglot Java and Python stacks.

Responsibilities

• Build and maintain end-to-end full-stack features connecting analyst-facing frontends with backend APIs and Java or Python microservices.
• Implement and optimize advanced RAG pipelines and stateful multi-agent workflows, incorporating structured outputs, tool calling, and human-in-the-loop steps.
• Implement automated offline and online evaluation suites to assess contextual relevance, groundedness, and hallucination reduction.
• Deploy and connect AI components with enterprise services on AWS, configuring Lambda, ECS/Fargate, EventBridge, S3, IAM policies, and API Gateway endpoints.
• Monitor model and service performance using CloudWatch and distributed tracing; triage production incidents, conduct root-cause analyses, and optimize token and resource consumption.
• Participate in peer code reviews, write automated unit and integration tests, maintain CI/CD pipelines, and document integration patterns and data models.
• Coordinate with business stakeholders and cross-functional teams in Agile sprints to translate research requirements into deliverable technical stories.

Benefits

• Goldman Sachs offers valuable and competitive benefits and wellness offerings. A benefits summary is available for active, non-temporary, full-time and part-time US employees who work at least 20 hours per week.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level