Senior Software Engineer

Red River•Raleigh, NC

12d•$159,910 - $195,680•Hybrid

About The Position

Red Hat is looking for a Senior Software Engineer to build backend systems with FastAPI (Python), develop multi-turn chatbots with agentic functionality using llama-stack and the OpenAI Agents SDK, and utilize NoSQL (MongoDB) and vector databases to persist and manage conversation data and application usage metrics. Telecommuting is permitted, with work performed within normal commuting distance from the Red Hat, LLC office in Raleigh, NC. The role involves designing, developing, testing, debugging, deploying, and maintaining application microservices for AI initiatives, working cross-functionally with teams on API development, and collaborating with data scientists to train, test, and evaluate AI models and LangFuse. The engineer will also manage the deployment of IBM Granite models with vLLM and monitor critical back-end services running in the cloud and in OpenShift clusters.

Requirements

Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Electronics Engineering or related field and five (5) years of experience in the job offered or related role OR Master's degree (U.S. or foreign equivalent) in Computer Science, Electronics Engineering or related field and three (3) years of experience in the job offered or related role.
Three (3) years of experience with: NoSQL or Vector databases for conversational data storage; observability and traceability of distributed applications; and containerization and deployment tools using Docker and Kubernetes.
Two (2) years of experience with: design and implementation of multi-turn conversational applications; and Python-based asynchronous web frameworks for building low latency application using distributed caching.
One (1) year of experience with Agentic Frameworks and LLM.

Responsibilities

Use Splunk for tracing logs, monitoring applications, and building rich dashboards.
Use Redis to cache user information and improve application latency.
Containerize applications with Docker for production deployments using Kubernetes.
Design, develop, test, debug, deploy and maintain application microservices for AI initiatives.
Work cross-functionally with teams on API development to support AI-based applications.
Work with data scientists to train, test and evaluate AI models and LangFuse.
Manage deployment of IBM Granite models with vLLM.
Monitor critical back-end services running in the cloud and in OpenShift clusters.