Java AI Lead / Enterprise Architect

We are seeking an experienced Java AI Lead / Enterprise Architect with strong banking and financial services expertise to drive enterprise architecture, Java-based application development, and AI-driven solution design. The ideal candidate will lead technical teams, define scalable architecture, integrate AI/ML capabilities into banking platforms, and ensure security, compliance, and performance across enterprise systems., Define and implement enterprise architecture and technical roadmaps for banking applications. Lead the design and development of scalable, high-performance Java applications using Spring Boot and microservices. Architect and integrate AI/ML solutions, Generative AI, and LLM-based applications into banking workflows. Evaluate AI use cases across fraud detection, risk management, customer experience, credit decisions, and operational automation. Design secure APIs, event-driven architectures, and integrations with core banking systems. Provide technical leadership, code reviews, design governance, and mentoring for development teams. Collaborate with business stakeholders, product owners, security teams, and enterprise architects. Ensure compliance with banking regulations, data privacy, security standards, and enterprise technology policies. Drive cloud adoption, DevOps practices, CI/CD automation, and application modernization initiatives.

Strong expertise in Java, Spring Boot, Spring Framework, microservices, and REST APIs. Proven experience in enterprise architecture, solution design, and large-scale distributed systems. Hands-on experience with AI/ML, Generative AI, LLMs, RAG, or AI-enabled enterprise applications. Strong understanding of banking systems, financial services workflows, and banking integrations. Experience with databases such as Oracle, PostgreSQL, or other enterprise database platforms. Knowledge of Kafka or similar messaging technologies and event-driven architecture. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Understanding of application security, authentication, authorization, and regulatory compliance. Excellent leadership, stakeholder management, communication, and problem-solving skills.

Preferred Qualifications Experience with AI frameworks and tools such as LangChain, vector databases, and enterprise AI platforms. Knowledge of MLOps, AI governance, model monitoring, and responsible AI practices. Exposure to core banking, payments, lending, risk, fraud prevention, or digital banking platforms. Experience with Kubernetes, Docker, Infrastructure as Code, and automated deployment pipelines. Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.