Senior Java Backend AI Engineer - Wealth Management

Role: Senior Java Backend & AI Engineer – Wealth Management (Move Money Platforms)

Location: Austin, TX or Westlake, TX (Hybrid – 3 days in office)

Permanent Department: Wealth Management Digital Platforms – Move Money Engineering

Experience Level: 8+ Years Enterprise Java Backend + AI/ML Integration

Rate: $50 - 55/hr on W2.

Core Responsibilities

• Backend Engineering: Design, build, and support high-throughput, fault-tolerant Java backend systems handling critical asset movement and real-time transaction processing.
  
• AI Platform Orchestration: Architect and deploy the backend infrastructure required to operationalize AI/ML models within the transactional pipeline, including LLM integration, intelligent agent routing, and automated decision engines.
  
• Predictive Transaction Workflows: Integrate deep learning and predictive modeling into Move Money operations to optimize liquidity predictions, dynamically route funds, and intelligently clear complex brokerage exceptions.
  
• Intelligent Security & Fraud Mitigation: Partner with data science and cybersecurity teams to inject AI-driven anomaly detection models directly into active payment streams, identifying and mitigating risk with sub-second latencies.
  
• System Modernization: Migrate legacy transactional applications to high-performance, cloud-native architectures utilizing microservices, event-driven designs, and automated CI/CD patterns.
  
• Data Pipeline & Engineering: Build resilient, asynchronous data streaming pipelines to aggregate high-fidelity transactional metadata, preparing and feeding data structures to train and evaluate AI models.
  
• Enterprise Collaboration: Act as the technical bridge between AI Data Science teams and core Financial Platform architects, ensuring secure, compliant, and performant production deployments.
  Technical Qualifications & Requirements
  Core Backend Capabilities
  
• Deep mastery of Java (Java 11 / 17 or later) and enterprise ecosystem development.
  
• Advanced experience with Spring Boot, Spring Cloud, Spring Security, and Hibernate/JPA frameworks.
  
• Proven expertise designing and scaling distributed systems, RESTful microservices, and high-volume transaction architectures.
  
• Robust understanding of event-driven software architectures using Apache Kafka or RabbitMQ.
  
• Strong relational database proficiency (Oracle, SQL Server) focusing on complex transactional consistency, ACID properties, and tuning.
  AI / ML Integration Capabilities
  
• Extensive experience serving and integrating AI/ML models in Java runtimes utilizing tools like LangChain4j, ONNX Runtime, or Deep Java Library (DJL).
  
• Hands-on practice orchestrating interactions with Large Language Models (LLMs) via secure Enterprise APIs for text summarization, data extraction, or automated reasoning.
  
• Familiarity with Vector Databases (such as pgvector, Pinecone, or Milvus) to support Retrieval-Augmented Generation (RAG) within financial applications.
  
• Practical experience collaborating with Python-based ML engineering environments and operational frameworks (MLflow, Kubeflow) to transition model weights into high-performance Java APIs.
  
• Familiarity with AI guardrails, model alignment testing, and architectural implementations that minimize hallucination or biases in transactional routing.
  Cloud, DevOps & Tooling
  
• Experience developing containerized deployments within enterprise cloud native infrastructure (Google Cloud Platform / GCP or Pivotal Cloud Foundry / PCF).
  
• Proficiency managing infrastructure deployments via Docker and Kubernetes environments.
  
• Expertise in continuous integration/delivery pipelines built using GitHub Actions, Bitbucket, or Bamboo.
  
• Rigorous standard for testing, adhering strictly to Test-Driven Development (TDD) or Behavior-Driven Development (BDD) paradigms with JUnit and Mockito.

Reach [email protected]

Pay: $50.00 - $55.00 per hour

Work Location: Hybrid remote in Austin, TX 78789