Duration: 5 years to start
Job Description
We are seeking a Java Developer (3-5 years) to join our team and contribute experience and technical expertise to our business logic and self-service support systems. You will be responsible for maintaining and migrating complex business rules using Drools and Kogito. Simultaneously building out our next-generation AI Chatbot infrastructure. A key focus of this role is the digital transformation of our legacy documentation (Adobe RoboHelp) into a high-performance Knowledge Base using AWS Bedrock and RAG (Retrieval-Augmented Generation) architectures.
Key Responsibilities:
- Business Automation: Design, develop, and maintain complex decision services using Drools (DRL) and migrate legacy workflows to cloud-native Kogito microservices.
- AI Implementation: Architect and manage AWS Bedrock Knowledge Bases, ensuring the LLM provides accurate, context-aware responses.
- Data Pipeline & ETL: Build automated pipelines to extract, clean, and convert legacy Adobe RoboHelp content into optimized Markdown/Vector formats stored in Amazon S3.
- Backend Development: Develop high-performance RESTful APIs using Quarkus or Spring Boot to integrate AI chatbot capabilities into our core Java applications.
- Cloud Orchestration: Deploy and scale business automation services within a Kubernetes/OpenShift environment.
Required Technical Skills:
- Java Mastery: 3-5 years of professional experience with Java (8/11/17+), including Spring Boot or Quarkus.
- Rule Engines: Hands-on experience writing and debugging Drools rules and implementing DMN (Decision Model and Notation).
- Cloud Native Automation: Proven experience with Kogito for building cloud-native business processes.
- AWS AI/ML Stack: Experience configuring AWS Bedrock (Knowledge Bases, Agents, or Prompt Engineering).
- **Proficiency in managing Amazon S3 for large-scale document storage and metadata tagging.
- Documentation Transformation: Experience (or strong scripting ability) in converting Adobe RoboHelp (HTML/XML) into structured formats (Markdown/JSON) for AI consumption.
- Modern DevOps: Experience with Git, CI/CD pipelines, and containerization (Docker/Kubernetes).
Preferred Qualifications:
- Experience with Vector Databases (Amazon OpenSearch, Pinecone, or Milvus).
- Understanding of Python (specifically for BeautifulSoup/Pandoc-based document parsing).
- Knowledge of BPMN 2.0 standards.
- AWS Certified Developer or AWS Machine Learning Specialty certification.
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