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# Solution Lead/ JAVA TECH LEAD

- **Company:** Connexions Data
- **Location:** Carolina Beach, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Software Debugging, Event-Driven Programming, Python (Programming Language), Performance Tuning, Search Technologies, Delivery Pipeline, Large Language Models, Concurrency, Caching, Backend, Rate Limiting, Fastapi, Kubernetes, Front End Software Development, Software Version Control, Microservices
- **Published:** August 11, 2026
- **Apply:** https://www.dice.com/job-detail/0ea94679-9e66-490d-b352-323829162ed7

## About the Role

Must Have Technical/Functional Skills

13+ years of experience with IT

Build and productionize cloud native backend services and AI/LLM inference pipelines.

Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph., Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.

## Description

Implement and optimize LLM capabilities including embeddings, RAG, vector search, prompt/context engineering, and model versioning.

Package, serve, and monitor models for real-time and batch inference, ensuring operational readiness and performance.

Build event driven, resilient integrations and containerized services, with hands-on Kubernetes debugging and Helm-based deployments.

Establish observability, SLOs, CI/CD automation, testing

Apply strong systems design principles (concurrency, caching, reliability, rate limiting) and robust data engineering practices.

Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.

Roles & Responsibilities

Build and productionize cloud native backend services and AI/LLM inference pipelines.

Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph.

Implement and optimize LLM capabilities including embeddings, RAG, vector search, prompt/context engineering, and model versioning.

Package, serve, and monitor models for real-time and batch inference, ensuring operational readiness and performance.

Build event driven, resilient integrations and containerized services, with hands-on Kubernetes debugging and Helm-based deployments.

Establish observability, SLOs, CI/CD automation, testing

Apply strong systems design principles (concurrency, caching, reliability, rate limiting) and robust data engineering practices.


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