Description

You will lead the modern evolution of core Move Money platforms within Wealth Management, building secure, scalable microservices and orchestrating AI infrastructure for intelligent transaction workflows.

This role is hybrid.

Responsibilities

• Design, build, and support high-throughput, fault-tolerant Java backend systems for critical asset movement and real-time transaction processing.
• Architect and deploy backend infrastructure to operationalize AI/ML models, including LLM integration, intelligent agent routing, and automated decision engines.
• Integrate deep learning and predictive modeling to optimize liquidity predictions, dynamically route funds, and clear complex brokerage exceptions.
• Partner with data science and cybersecurity teams to inject AI-driven anomaly detection models into active payment streams for sub-second risk mitigation.
• Migrate legacy transactional applications to high-performance, cloud-native architectures using microservices, event-driven designs, and automated CI/CD.

Required Skills

• 6+ years of enterprise Java backend development with deep mastery of Java 11/17 or later.
• 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.
• Strong 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.
• Experience serving and integrating AI/ML models in Java runtimes using tools like LangChain4j, ONNX Runtime, or Deep Java Library (DJL).
• Hands-on practice orchestrating interactions with Large Language Models (LLMs) via secure Enterprise APIs.
• Familiarity with Vector Databases (pgvector, Pinecone, or Milvus) to support Retrieval-Augmented Generation (RAG).

Preferred Skills

• Practical experience collaborating with Python-based ML engineering environments and operational frameworks (MLflow, Kubeflow).
• Familiarity with AI guardrails, model alignment testing, and architectural implementations that minimize hallucination or biases.

Key Skills

Education

Any Graduate