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

- **Company:** The Goldman Sachs Group Inc
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $150,000 - $300,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Databases, Extract Transform Load (ETL), Gradle, Java Persistence API, Java Virtual Machine (JVM), Apache Maven, RabbitMQ, Software Engineering, SQL Databases, Systems Integration, Data Logging, Pinecone, Retrieval-Augmented Generation, Large Language Models, Spring-boot, Sybase, Generative AI, Agentic-AI, Information Technology, Weaviate, Apache Kafka, Milvus, Machine Learning Operations, Virtual Agents, Model Inference, Human in the Loop, Microservices
- **Published:** October 18, 2026
- **Apply:** https://diversityjobs.com/career/18682889/Ai-Ml-Engineer-Global-Banking-Markets-Ria-Engineering-New-York-New-York

## About the Role

* Core Java: Expert-level proficiency in Java 21+ (utilizing Virtual Threads/Project Loom for high-concurrency AI inference).
 * AI Frameworks: Hands-on experience with leading AI frameworks / tools.
 * Enterprise Stack: Deep experience with Spring Boot 3.x, JPA, Sybase, and Maven/Gradle.
 * Data & Search: Proficiency in SQL and integration with enterprise vector stores (e.g., Milvus, Weaviate, or Pinecone) via Java clients.
 * Messaging & Integration: Experience with Apache Kafka or RabbitMQ for orchestrating asynchronous AI agent tasks.
 * Cloud Infrastructure: Deployment experience on AWS using SDKs., * Experience: 6+ years in Java software engineering, with at least 3 years focused on AI/ML integration in production.
 * Domain Knowledge: Understanding of RIA workflows, collateral eligibility, and the regulatory landscape of asset-based lending.
 * Education: Degree in Computer Science, Financial Engineering, or a related field.

## Description

We are seeking a Senior AI Engineering Expert with deep expertise in leveraging the latest and greatest AI tooling to drive developing solutions on the Java/JVM based ecosystem. You will be responsible for architecting and implementing production-grade AI solutions that integrate directly into our existing Java-based microservices. Your primary focus will be on building scalable, type-safe, and observable AI "Agentic" workflows that automate collateral management, risk monitoring, and advisor support., * System Integration: Architect and implement end-to-end AI pipelines (RAG, Agentic workflows) that integrate seamlessly with existing enterprise APIs, legacy databases, and microservices.

 * Scalability & Performance: Optimize inference latency and manage token costs for large-scale deployments serving thousands of internal and external users.
 * Evaluation & Governance: Establish robust evaluation frameworks to measure model accuracy, mitigate hallucinations, and ensure compliance with enterprise security and privacy standards.
 * Cross-Functional Leadership: Collaborate with tech leads, security leads, and software teams to identify high-impact AI use cases and define technical roadmaps.
 * Continuous Innovation: Stay at the forefront of Generative AI, multimodal models, and autonomous agents, recommending strategic pivots as the technology evolves.
 * Enterprise RAG Pipelines: Build robust Retrieval-Augmented Generation (RAG) systems using Java-based ETL pipelines to ingest and index unstructured custodial data (e.g., legal agreements, market news) into vector databases.
 * Performance & Observability: Leverage Spring Boot Actuator and Micrometer to monitor LLM latency, token usage, and model drift within our standard enterprise monitoring stack.
 * Regulatory Compliance (Audit-by-Design): Implement "Human-in-the-Loop" (HITL) patterns and structured logging to ensure all AI-driven lending decisions are explainable and compliant with 2026 SEC/FINRA standards.
 * System Modernization: Lead the transition of traditional batch-oriented Java processes to real-time, event-driven AI architectures using AWS MSK and similar tools.