Job description

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. Who We Look For 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. How You Will Fulfill Your Potential • 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. Required Technical Skills • 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. Qualifications • 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. Please note we will only respond to applications for which we have an interest. Salary Range The expected base salary for this New York, New York, United States-based position is $150,000-$300,000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end. Benefits Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. 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 .

Requirements

Must-haves

Who We Look For
How You Will Fulfill Your Potential
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.
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.
Required Technical Skills
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.
Please note we will only respond to applications for which we have an interest.

Nice-to-haves

The expected base salary for this New York, New York, United States-based position is $150,000-$300,000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Application prep

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Keywords to mirror

machine learningaijavallmawssqlml

Platform: goldman-sachs
Effort: medium

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