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

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 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.

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.

• 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.

• 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…