About the job
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 to join our technology team supporting RIA Custody and Security-Based Lending (SBL) platforms. 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.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
No preferred qualifications listed.