Lead AI Platform Developer (Java, Backend & Agentic AI/LLM) )

We are seeking a Senior Software Engineer to lead backend development for our cutting-edge, multi-tenant Enterprise AI Assistant Platform. In this role, you will design and scale robust microservices that power multi-LLM routing, real-time streaming, and cross-device synchronization. You will work at the intersection of reactive programming, strict multi-tenant database architecture, and advanced AI tool integrations to deliver a secure, highly responsive chat experience at an enterprise scale., Reactive & Real-Time Systems: Develop non-blocking, real-time AI chat capabilities using Spring WebFlux, R2DBC, and Server-Sent Events (SSE) to stream AI responses without exhausting server threads. Multi-Tenant Architecture: Architect dynamic database routing and automated schema migrations across distinct, dynamically provisioned PostgreSQL tenant databases using Flyway to ensure ironclad data isolation. AI & LLM Integration (Adapter Pattern): Build provider-agnostic adapter interfaces to seamlessly route requests across multiple LLM providers (e.g., Azure OpenAI, standard OpenAI, LiteLLM) to prevent vendor lock-in. Platform Engineering: Design and implement highly scalable backend microservices using Java 17 (or Kotlin) and Spring Boot 3.x. Extensibility & Tooling: Implement Model Context Protocol (MCP) servers and tools, alongside Retrieval-Augmented Generation (RAG) and Vector Store capabilities (AWS S3), to extend the AI’s reasoning and secure access to company data. Security & Identity: Secure APIs and SDKs implementing robust authentication flows, including JWT Bearer Tokens, HMAC request signing, and Role-Based Access Control (RBAC).

Extensive experience building enterprise applications with Java 17 and/or Kotlin. Crucial: Deep expertise in reactive programming using Spring WebFlux and Project Reactor (Mono/Flux). Crucial: Experience with reactive database drivers, specifically R2DBC, rather than traditional blocking JDBC/JPA. Proven track record of designing secure, multi-tenant backend architectures with tenant-level database isolation and dynamic routing. Experience configuring and deploying cloud services, specifically AWS S3 (pre-signed URLs) and AWS Secrets Manager.

Preferred Qualifications:

Experience integrating generative AI models and external tooling frameworks (e.g., Spring AI, MCP, LangChain). Familiarity with modern observability tools (Prometheus, Micrometer, Spring Actuator).