Allianz - Senior Developer - Java Technologies

Description : About The Role : We are seeking a highly skilled Senior Developer with strong hands-on experience in Java, Spring Boot, Kafka, and NoSQL databases now expanded to include AI/ML engineering capabilities. The ideal candidate will design, develop, and maintain high-performance, scalable applications while integrating AI-powered features into enterprise insurance systems. Experience in the Insurance domain will be a strong advantage. Experience : 5+ Years. Primary Stack : Java / Spring Boot. AI Focus : LLM Integration. Domain : Insurance. Key Responsibilities : - Design, develop, and enhance backend services and APIs using Java and Spring Boot. - Build high-throughput and resilient event-driven components using Kafka. - Work with MongoDB or other NoSQL databases to design efficient data models and optimize queries. - Integrate Large Language Models (LLMs) such as OpenAI, Claude, or Gemini into backend services via REST APIs and SDKs. - Build and maintain AI-powered microservices including RAG (Retrieval-Augmented Generation) pipelines, semantic search, and document intelligence features. - Develop and expose AI agent workflows using frameworks such as LangChain4j, Spring AI, or similar Java-native AI toolkits. - Implement prompt engineering strategies, context management, and output validation layers for LLM interactions. - Design vector database integrations (Pinecone, Weaviate, pgvector) for embedding storage and similarity search. - Collaborate closely with architects, BAs, and cross-functional teams to deliver robust technical solutions. - Participate in code reviews, refactoring efforts, and optimisation of system performance. - Ensure best practices for coding standards, security, maintainability, and AI model governance. - Troubleshoot production issues and provide root cause analysis and long-term fixes. - Support CI/CD pipeline integration, model deployment automation, and MLOps tooling. - Contribute to documentation, technical specifications, and architectural diagrams. Required Skills & Qualifications : - 5+ years of hands-on development experience in Java-based applications. - Strong expertise in Java (8/11/17), Spring Framework, Spring Boot, and RESTful services. - Experience with Kafka for messaging, streaming, or event-driven architecture. - Practical knowledge of MongoDB or other NoSQL databases (e.g., Cassandra, DynamoDB, Couchbase). - Solid understanding of microservices architecture and distributed systems. - Hands-on experience consuming LLM APIs (OpenAI GPT-4o, Anthropic Claude, Google Gemini) in production Java applications. - Familiarity with Spring AI or LangChain4j for building LLM-backed services in Java ecosystems. - Experience with prompt engineering crafting, versioning, and testing prompts for accuracy, safety, and cost efficiency. - Knowledge of embedding models and vector stores for semantic search and RAG pipelines. - Strong debugging, analytical, and problem-solving skills. - Experience with Git, Maven/Gradle, Jenkins, Docker, or Kubernetes is a plus. - Excellent communication and collaboration skills. Preferred Skills : - Experience working in the Insurance domain (Policy, Claims, Underwriting, Billing, etc.) - Hands-on experience building or fine-tuning ML models using Python-based frameworks (Hugging Face, scikit-learn, PyTorch) integrated with Java services. - Exposure to AI agent orchestration tools LangGraph, AutoGen, CrewAI, or OpenAI Assistants API. - Experience deploying models on cloud AI services : AWS Bedrock, Azure OpenAI Service, or Google Vertex AI. - Familiarity with MLOps platforms (MLflow, SageMaker, Kubeflow) for experiment tracking and model lifecycle management. - Knowledge of AI safety, responsible AI practices, and PII/data privacy considerations when working with LLMs. - Exposure to cloud platforms such as AWS, Azure, or GCP. - Knowledge of caching frameworks (Redis, Hazelcast) for LLM response caching and rate-limit management. - Familiarity with containerization and orchestration platforms. - Understanding of DevOps principles and observability tools (Grafana, Prometheus, ELK) including LLM observability (token usage, latency, hallucination monitoring). Ai / Ml Skills Highlight : - LLM Integration : OpenAI, Claude API, Gemini, Azure OpenAI. - Java AI Toolkits : Spring AI, LangChain4j. - Prompt Engineering : Prompt design, versioning, A/B testing. - Vector Databases : Pinecone, Weaviate, pgvector. - RAG Pipelines : Embedding models, semantic search. - MLOps : MLflow, SageMaker, Hugging Face Hub. WHY JOIN US : - Opportunity to work on scalable, enterprise-level backend systems enhanced with cutting-edge AI capabilities. - A collaborative environment with strong engineering, AI research, and domain experts. - Continuous learning and growth opportunities through challenging technical projects at the intersection of Java and AI. - Dedicated AI innovation time and access to