Java AI Developer

As a Senior Java AI Developer, you will lead AI-focused workflows across the System Development Life Cycle. You will work at the dynamic intersection of Java engineering, event-driven architectures, cloud-native platforms, and Generative AI-assisted delivery. Your primary objective will be to build intelligent, highly reliable systems that support complex business capabilities and deliver value to clients within a leading financial services organization. You will leverage cutting-edge AI coding tools to reduce context switching and accelerate delivery, all while maintaining rigorous ownership over code correctness, quality, and engineering validation.

Responsibilities

Lead the design and development of Java-based, cloud-native, event-driven applications that are scalable, resilient, observable, and performant.

Build and modernize services utilizing Java, Spring Boot, Kafka, REST APIs, CI/CD pipelines, container platforms, and distributed system patterns.

Partner with architects, developers, product owners, and cross-functional teams to translate business capabilities into high-quality technical solutions.

Utilize GenAI-assisted development tools to accelerate implementation, refactoring, unit testing, documentation, troubleshooting, and engineering workflow improvements.

Establish responsible AI-assisted development practices, creating reusable prompts, custom instructions, review expectations, and team-level adoption strategies.

Drive engineering quality through code reviews, automated testing, observability, resiliency validation, performance tuning, and production readiness practices.

Mentor engineers on Java engineering standards, distributed architecture, cloud-native design, event streaming, and AI-augmented SDLC practices.

Contribute to enterprise modernization initiatives by migrating legacy capabilities toward distributed Java services and cloud-native operating models.

Bachelor’s degree in Computer Science, Software Engineering, a related technical field, or equivalent practical experience.

7 years of professional software engineering experience developing scalable, high-performance Java, cloud-based, and web services applications for high-volume environments.

6 years of experience building and deploying cloud-native applications using Google Cloud Platform, Docker, Kubernetes, microservices, and CI/CD practices.

2 years of experience working with databases such as MongoDB, Aerospike, PostgreSQL, Oracle, or comparable platforms.

2 years of experience driving IT transformation and system modernization from legacy platforms to distributed Java, cloud-native, and event-driven architectures.

2 years of hands-on experience with AI/ML implementation, AI-assisted engineering practices, or production deployment of AI-enabled solutions.

Experience leading the design and implementation of scalable applications using Java, Spring Boot, Kafka, and cloud deployments (e.g., PCF, AWS, Google Cloud Platform).

Experience acting as a technical lead, owning solution design, engineering standards, code review practices, and technical delivery.

Experience using Generative AI coding assistants (e.g., GitHub Copilot, Claude Code) across SDLC workflows, including implementation, testing, and automation.

Experience designing RESTful services, asynchronous message flows, and messaging platforms (e.g., Kafka, IBM MQ) alongside observability tools (e.g., Splunk).

Experience in an Agile working environment utilizing the Atlassian tool stack (Jira, Confluence).

Experience with broker-dealer capabilities, financial operations, or the broader financial services industry.

Preferred qualifications:

Master’s degree in Information Technology, Computer Science, Software Engineering, Artificial Intelligence, or a related field.

Experience with Retrieval-Augmented Generation (RAG), vector databases, AI orchestration patterns, or enterprise AI platform integration.

Experience with Test-Driven Development (TDD), Behavior-Driven Development (BDD), QA automation, and quality engineering principles.

Experience with Spring Cloud, Spring Security, reactive programming, API gateways, or service mesh.

Experience with performance engineering, reliability testing, resiliency testing, and operational readiness for high-volume distributed platforms.

Proficiency in creating architecture diagrams, design documentation, technical specifications, runbooks, and test environment documentation.