Senior AI Engineer, Global Banking & Markets, RIA Engineering

Goldman Sachs • New York, NY

3h • Onsite

About The Position

At Goldman Sachs, Engineers don't just make things – they make things possible. They change the world by connecting people and capital with ideas, solving challenging engineering problems for clients. The engineering teams build massively scalable software and systems, architect low latency infrastructure solutions, guard against cyber threats, and leverage machine learning alongside financial engineering to turn data into action. In an era defined by AI, Engineering is the driving force behind the business, demanding innovative strategic thinking and immediate, impactful solutions. The firm is seeking a Senior AI Engineering Expert with deep expertise in leveraging the latest AI tooling to develop solutions on the Java/JVM based ecosystem, supporting RIA Custody and Security-Based Lending (SBL) platforms. This role involves architecting and implementing production-grade AI solutions that integrate directly into existing Java-based microservices, with a primary focus on building scalable, type-safe, and observable AI "Agentic" workflows that automate collateral management, risk monitoring, and advisor support.

Requirements

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

Responsibilities

• Architect and implement end-to-end AI pipelines (RAG, Agentic workflows) that integrate seamlessly with existing enterprise APIs, legacy databases, and microservices.
• Optimize inference latency and manage token costs for large-scale deployments serving thousands of internal and external users.
• Establish robust evaluation frameworks to measure model accuracy, mitigate hallucinations, and ensure compliance with enterprise security and privacy standards.
• Collaborate with tech leads, security leads, and software teams to identify high-impact AI use cases and define technical roadmaps.
• Stay at the forefront of Generative AI, multimodal models, and autonomous agents, recommending strategic pivots as the technology evolves.
• 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.
• Leverage Spring Boot Actuator and Micrometer to monitor LLM latency, token usage, and model drift within our standard enterprise monitoring stack.
• 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.
• Lead the transition of traditional batch-oriented Java processes to real-time, event-driven AI architectures using AWS MSK and similar tools.

Benefits

• Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here [https://www.goldmansachs.com/careers/discover/2022-Benefits-Summary-US.pdf].

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees