Solution Lead/ JAVA TECH LEAD

Connexions Data

Carolina Beach, NC, United States

2 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

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

+10 more

Large Language Models Concurrency Caching Backend Rate Limiting Fastapi Kubernetes Front End Software Development Software Version Control Microservices

Job 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.

Requirements

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.