AI/ML Engineer, Global Banking & Markets, RIA Engineering

Goldman Sachs

Confirmed live today High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$150,000–$300,000 / yr
Posted
7 days ago
Freshness
Confirmed live today

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Competitive pay

How this pay compares to similar roles

Similar $212k
This role $225k
$132k $318k
below market most similar roles pay here above market

This role pays more than 61% of similar roles. Most pay $169,625–$254,750 — the blue band above. At the midpoint, this role pays about $225k versus about $212k for comparable roles.

Based on 240 similar postings.

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About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 71 open roles on FindRole.

Listed pay typically runs $140,000–$250,000 across 34 roles with salary data.

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At a glance

TL;DR · AI/ML Engineer, Global Banking & Markets, RIA Engineering

AI/ML Engineer, Global Banking & Markets, RIA Engineering joins the RIA Engineering team as a Senior AI Engineering Expert. This role involves architecting and implementing production-grade AI solutions, specifically building scalable, type-safe, and observable AI Agentic workflows to automate collateral management, risk monitoring, and advisor support. You will build end-to-end AI pipelines, including Retrieval-Augmented Generation systems, and transition batch-oriented processes to real-time, event-driven architectures. The position requires expert-level proficiency in Java 21+, Spring Boot 3.x, JPA, Sybase, Maven, and Gradle. You will utilize AWS, Apache Kafka, RabbitMQ, and SQL to integrate with vector stores like Milvus or Pinecone. Key responsibilities include optimizing inference latency, managing token costs, and ensuring regulatory compliance for AI-driven lending decisions within the RIA and asset-based lending domain.

What you'll do

  • Architect and implement end-to-end AI pipelines including RAG and Agentic workflows within a Java-based microservices ecosystem.
  • Build robust Retrieval-Augmented Generation (RAG) systems using Java-based ETL pipelines to index unstructured data into vector databases.
  • Optimize inference latency and manage token costs for large-scale deployments serving thousands of users.
  • Establish evaluation frameworks to measure model accuracy, mitigate hallucinations, and ensure compliance with security standards.
  • Monitor LLM latency, token usage, and model drift using Spring Boot Actuator and Micrometer.
  • Implement "Human-in-the-Loop" patterns and structured logging to ensure AI-driven lending decisions are explainable and compliant.
  • Lead the transition of batch-oriented Java processes to real-time, event-driven AI architectures using AWS MSK.

What we're looking for

  • Degree in Computer Science, Financial Engineering, or a related field.
  • 6+ years of experience in Java software engineering.
  • At least 3 years of experience focused on AI/ML integration in production.
  • Expert-level proficiency in Java 21+ including Virtual Threads and Project Loom.
  • Hands-on experience with leading AI frameworks and tools.
  • Deep experience with Spring Boot 3.x, JPA, Sybase, and Maven/Gradle.
  • Proficiency in SQL and integration with enterprise vector stores via Java clients.
  • Experience with Apache Kafka or RabbitMQ and deployment on AWS using SDKs.

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