Quick overview
SeniorityMid Senior
Work modeOn Site
LocationDallas, TX, United States
SpringSpring BootAWSLogstashGPTHibernateJWTJavaKotlinLLMPrometheusGenerative AIAzurePostgreSQLRAG
Job description
Job Title: Java Backend Engineer
Location: Dallas, TX
Duration: Long-term
Work Mode: Onsite
Required experience: 13+ Years
Required Telecom domain experience
Key Responsibilities:
- Platform Engineering: Design and implement highly scalable backend services using Java 17, Kotlin 1.9.25, and Spring Boot 3.5.11.
- Reactive & Real-Time Systems: Develop non-blocking, real-time AI chat capabilities using Spring WebFlux, R2DBC, and Server-Sent Events (SSE) within the Shannon Agent Server.
- Multi-Tenant Architecture: Architect dynamic database routing and auto-migrations across distinct PostgreSQL tenant databases using Flyway.
- AI & LLM Integration: Build adapter-pattern interfaces to seamlessly route requests across multiple LLM providers, including Azure OpenAI, OpenAI (GPT API v4.9), and LiteLLM.
- Extensibility & Tooling: Implement Model Context Protocol (MCP) servers and tools, alongside RAG and Vector Store capabilities, to extend the platform's AI reasoning.
- Security & Identity: Secure APIs and SDK configurations implementing robust authentication flows, including JWT Bearer Tokens, HMAC request signing, and Role-Based Access Control (RBAC).
- Data & State Management: Build multi-device sync, chat backup/restore, and secure file handling utilizing AWS S3 and pre-signed URLs within the Shannon Sync Server.
Required Qualifications:
- Extensive experience building enterprise applications with Java 17 and Kotlin.
- Deep expertise in the Spring ecosystem, specifically Spring Boot 3.5+, Spring MVC, and reactive paradigms using Spring WebFlux.
- Strong background in data modeling and database interaction using PostgreSQL, JPA, Hibernate Envers, and reactive drivers like R2DBC.
- Proven track record of designing secure, multi-tenant backend architectures with tenant-level isolation.
- Experience configuring and deploying cloud services, specifically AWS S3 for object storage and AWS Secrets Manager for runtime credential management.
- Familiarity with modern observability and telemetry tools, including Prometheus, Micrometer, Logstash
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