Generative AI Java Developer

Job Description - Generative AI Java Developer
Location - Plano, TX
Role Summary
We are seeking a highly skilled Generative AI Java Developer with strong expertise in AWS Bedrock, Large Language Models (LLMs), and enterprise Java application development to design and deliver next generation AI powered solutions. The ideal candidate will have extensive experience in building scalable, cloud native applications and integrating Generative AI capabilities into enterprise platforms, particularly within the banking and financial services domain. In this role, you will architect and develop AI agent frameworks, implement Retrieval Augmented Generation (RAG) solutions, fine tune and deploy foundation models on AWS Bedrock, and integrate AI driven features into modern microservices based applications. You will leverage technologies such as Java 8/11/17, Spring Boot, Spring AI, Python, Kafka, React JS, LangChain, OpenAI GPT APIs, Hugging Face Transformers, Docker, Kubernetes, and AWS
services including EC2, S3, Lambda, and SageMaker. The position requires strong expertise in microservices architecture, RESTful APIs, event driven systems, vector databases, and AI/ML lifecycle management tools such as MLflow and Kubeflow. You will collaborate with cross functional teams including data scientists, product managers, and engineers to transform AI research into production grade solutions while ensuring performance, scalability, security, and cost optimization. The successful candidate will also drive engineering excellence through best practices such as TDD, BDD, and Domain Driven Design
(DDD), mentor development teams, and lead the adoption of innovative AI and software engineering practices. Candidates should possess at least 8 years of experience in enterprise Java development and AI/ML engineering, with a proven track record of deploying Generative AI and machine learning solutions into production environments, along with hands on experience in cloud native architectures, Kafka based integrations, and modern DevOps practices.