FullStack Java Engineer

Responsibilities

• Build and maintain backend services using Java 21, Spring Boot, and asynchronous processing patterns.
• Design and enhance LLM-based pipeline stages for classification, matching, risk assessment, summarization, and draft generation.
• Implement robust structured output validation, retry mechanisms, and error handling for model interactions.
• Optimize semantic search using PostgreSQL and pgvector to enable high-quality retrieval of legal precedents.
• Extend data models and database migrations with backward-compatible schema changes.
• Build and enhance frontend workflows using React and TypeScript, including dashboards, document browsers, extraction review interfaces, and defense generation features.
• Integrate real-time progress updates through WebSockets.
• Maintain secure authentication and authorization using Keycloak, OIDC, and JWT.
• Develop and maintain backend and frontend test coverage while supporting CI quality gates.
• Improve observability through distributed tracing, structured logging, and operational dashboards.

Qualifications

• 5+ years of software engineering experience working on production systems. • Strong experience in Java backend development, including Spring Boot, REST APIs, and data access layers.
• Solid PostgreSQL expertise, including schema design and query optimization. • Hands-on experience integrating LLM APIs (OpenAI, Azure OpenAI, Anthropic, or similar).
• Experience with semantic search and vector retrieval technologies (pgvector, Pinecone, Weaviate, or similar).
• 3+ years of experience with React and TypeScript development.
• Practical experience implementing OAuth, OIDC, and JWT authentication and authorization flows.
• Strong testing discipline, including unit, integration, API, and contract testing.

Nice to have

• Experience with Azure services, including Azure OpenAI, Document Intelligence, PostgreSQL, and Container Apps.
• Experience with Docker, Docker Compose, and CI/CD pipelines.
• Domain knowledge in legal tech, financial services, or other highly regulated industries.
• Familiarity with observability stacks, including OpenTelemetry, centralized logging, and monitoring dashboards.
• Familiarity with LLM evaluation, guardrails, and regression testing tools such as Promptfoo, DeepEval, Langfuse, Giskard, or Guardrails.