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Goldman Sachs in Bengaluru seeks a Global Investment Research - Associate-Software Engineering to join an on-site team building scalable software and intelligent tools. You will work on end-to-end full-stack features using Java or Python, React, and microservices, with a focus on AI-enabled research workflows.
The role emphasizes Gen AI, agentic pipelines, and deployment on AWS, with collaboration in Agile sprints.
What We Do At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Drive new businesses, redefine finance using AI, and seize opportunities at market speed. In an era defined by AI, Engineering isn't just central – it's the driving force behind our business. Our dynamic environment demands innovative strategic thinking and immediate, impactful solutions. Ready to push the limits of digital possibility? Begin your journey here.
Goldman Sachs Global Investment Research (GIR) is seeking an Agentic Systems Engineer to build, enhance, and productionize intelligent research tools and automated agentic pipelines. You will collaborate with senior engineers to develop end-to-end full-stack applications, implement advanced RAG components, and integrate AI services into mission-critical GIR platforms.
Build and maintain end-to-end full-stack features, integrating analyst-facing frontends with backend APIs and microservices implemented in Java or Python.
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.
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.
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/resource consumption.
Actively 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.
Experience Level Mid Level.
Please note we will only respond to applications for which we have an interest.