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

- **Company:** SSE
- **Location:** Irving, TX, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Databases, System Configuration, Java Database Connectivity, Java Persistence API, Spring Framework, PostgreSQL, Role-Based Access Control, OpenAI, Cloud Services, Prometheus, Data Streaming, Dynamic Routing, Enterprise Software Applications, Real Time Systems, Large Language Models, Grafana, Spring-boot, Generative AI, Backend, Agentic-AI, Kotlin, AI Platforms, Reactive Programming, LiteLLM, Virtual Agents, Model Context Protocol, Microservices
- **Published:** October 28, 2026
- **Apply:** https://www.dice.com/job-detail/0f368050-6f75-4f95-aab8-f5c0b81dea8b

## About the Role

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).

## Description

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).