Agentic Systems Engineer for Gen AI in Investment Research

Goldman Sachs; West Midlands; Presencial; GBP 90.000 - 140.000; Tempo integral

Resumo da vaga

Goldman Sachs is seeking an Agentic Systems Engineer to build and productionize intelligent tools and agentic pipelines. Collaborate with senior engineers to develop end-to-end full-stack apps, implement RAG components, and integrate AI services into GIR platforms.

You will work on feature engineering, Gen AI implementation, evaluation pipelines, and cloud data integration with AWS services, while adhering to SDLC discipline and Agile practices.

Qualificações

• 7+ years of hands-on software engineering experience with Java or Python and modern full-stack technologies.
• Bachelor’s degree in Computer Science, Software Engineering, Applied Mathematics, or a related field.
• Working knowledge of core AWS services (Lambda, ECS/Fargate, S3, EventBridge, CloudWatch, API Gateway).

Responsabilidades

• Build and maintain end-to-end full-stack features with frontends and microservices in Java or Python.
• Implement and optimize Gen AI pipelines and multi-agent workflows.
• Evaluate with automated offline and online tests and benchmarks.
• Deploy AI components to AWS services and ensure smooth data integration.
• Monitor performance, triage incidents, and optimize resource consumption.
• Contribute to CI/CD pipelines and document integration patterns.

Conhecimentos

Java

Python

React

TypeScript

FastAPI

Spring Boot

Distributed systems

Formação

Bachelor's degree in Computer Science or related

Ferramentas

AWS Lambda

ECS/Fargate

S3

EventBridge

CloudWatch

API Gateway

Docker

Git

CI/CD

Descrição da vaga

Goldman Sachs is seeking an Agentic Systems Engineer to build and productionize intelligent tools and agentic pipelines. Collaborate with senior engineers to develop end-to-end full-stack apps, implement RAG components, and integrate AI services into GIR platforms.

You will work on feature engineering, Gen AI implementation, evaluation pipelines, and cloud data integration with AWS services, while adhering to SDLC discipline and Agile practices.