Python AI Solutions

Centraprise; Cary (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

Centraprise in Cary, NC is hiring a backend AI engineer to build cloud-native services and productionize AI/LLM pipelines. You will design Python APIs and microservices using FastAPI with async patterns and craft agentic AI workflows via LangChain/LangGraph.

You will implement embeddings, RAG, vector search, and model versioning, while packaging, serving, and monitoring models for real-time and batch workloads. Expect Kubernetes deployments and robust data engineering practices.

Qualifications

• Proficient in Python with API/microservices development.
• Experience designing scalable AI/LLM workflows and API patterns.
• Strong understanding of LLM capabilities (embeddings, RAG, vector search).

Responsibilities

• Build and productionize cloud-native backend services and AI/LLM pipelines.
• Design Python APIs and microservices (FastAPI, async patterns) for agentic workflows.
• Implement and optimize LLM features including embeddings, RAG, and model versioning.
• Package, serve, and monitor models for real-time and batch inference.
• Develop resilient, event-driven integrations and Kubernetes-based deployments.

Skills

Python

FastAPI

Async patterns

LLM workflows

LangChain/LangGraph

Embeddings

RAG

Vector search

Prompt engineering

Model versioning

Concurrency

Caching

Reliability

Rate limiting

Data engineering

Kubernetes

Helm

Azure

AKS

Performance tuning

Frontend collaboration

Model governance/monitoring

Tools

LangChain

LangGraph

Azure AKS

Helm

Job description

• 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.
• 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.
• 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.
• 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.

"Centraprise is an equal opportunity employer. Applicants must be authorized to work in the U.S. U.S. citizens and Green Card holders are strongly encouraged to apply"