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# Software Engineer, Global Investment Research, Agentic Systems - Associate

- **Company:** The Goldman Sachs Group Inc
- **Location:** Dallas, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Automation of Tests, Cloud Computing, System Configuration, Data Integration, Data Security, Enterprise Content Management, Identity and Access Management, Python (Programming Language), Scrum Methodology, Systems Development Life Cycle, Software Engineering, TypeScript, Feature Engineering, LangChain, ReactJS, Evaluation Pipelines, Retrieval-Augmented Generation, Multi-Agent Systems, Prompt Engineering, Spring-boot, Hallucination Detection, Caching, AgentCore, Generative AI, Agentic-AI, Git, Fastapi, Servicebus, Information Technology, AWS Fargate, Web Technologies, Cloudwatch, Api Gateway, Dynatrace, Docker, Web Api, Microservices
- **Published:** October 27, 2026
- **Apply:** https://diversityjobs.com/career/18781445/Software-Engineer-Global-Investment-Research-Agentic-Systems-Associate-Texas-Dallas

## About the Role

* Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.
 * 3-5 years of hands-on software engineering experience with proficiency in Java or Python, combined with modern full-stack web technologies (e.g., React, TypeScript, FastAPI, Spring Boot).
 * Practical experience building Gen AI applications using Google ADK, LangGraph, or equivalent agentic frameworks, vector databases, and AWS Bedrock.
 * Experience implementing evaluation pipelines and prompt testing with Braintrust, AgentCore Eval, equivalent technologies, or custom benchmark harnesses.
 * Working knowledge of core AWS services, including Lambda, ECS/Fargate, S3, EventBridge, CloudWatch, and API Gateway.
 * Solid understanding of standard SDLC tooling, automated testing, Git, Docker, and CI/CD automation., * 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 defending against prompt injection and unauthorized data access.
 * Experience building asynchronous or event-driven microservices across polyglot Java and Python stacks.

## Description

* Feature Engineering: Build and maintain end-to-end full-stack features, integrating analyst-facing frontends with backend APIs and microservices implemented in Java or Python.
 * Gen AI & Agent Implementation: Implement and optimize advanced RAG pipelines and stateful multi-agent workflows using Google ADK, LangChain, LangGraph, AWS Bedrock, or equivalent technologies, incorporating structured outputs, tool calling, and human-in-the-loop steps.
 * Evaluation & Benchmarking: Implement automated offline and online evaluation suites using tools such as Braintrust, AgentCore Eval, equivalent industry solutions, or custom test harnesses to assess contextual relevance, groundedness, and hallucination reduction.
 * Cloud & Data Integration: Deploy and connect AI components with enterprise services on AWS, configuring Lambda, ECS/Fargate, EventBridge, S3, IAM policies, and API Gateway endpoints.
 * Observability & Incident Support: Monitor model and service performance using CloudWatch and distributed tracing; triage production incidents, conduct root-cause analyses, and optimize token/resource consumption.
 * SDLC Discipline: Actively participate in peer code reviews, write automated unit and integration tests, maintain CI/CD pipelines, and document integration patterns and data models.
 * Agile Collaboration: Coordinate with business stakeholders and cross-functional teams in Agile sprints to translate research requirements into deliverable technical stories.