Senior AI Software Engineer – Onsite, LLM/RAG, Cloud

ECPI University LLC; Virginia Beach (VA); On-site; USD 100,000 - 120,000; Full time

Benefits offered by this job

Tuition scholarship

401(k) plan

Full benefits

Job summary

ECPI University is seeking an experienced software engineer to support the Director of AI and Analytics in building ECPI's proprietary AI suite. The role focuses on LLM applications, RAG pipelines, vector storage, and cloud-native services using Azure and AWS.

You will design multi-platform AI applications, oversee the full development lifecycle, and deliver scalable tools for faculty, staff, and students. Robust cloud experience and AI/LLM development are essential.

Qualifications

• Bachelor's degree in a relevant field or related experience.
• 6+ years of software engineering experience in software development and cloud-based applications.
• 2+ years of experience with AI/LLM application development.
• 2+ years of experience in AI Assisted coding.

Responsibilities

• Support the Director of AI and Analytics and work with other developers to build and maintain ECPI University's proprietary AI suite.
• Focus on LLM applications, RAG systems, vector storage, and cloud native services in Azure and AWS.
• Design and develop multi-platform AI applications using cloud architecture.
• Build LLM-powered tools for faculty, staff, and students using Azure AI Foundry, AWS Bedrock, OpenAI APIs, and related cloud AI services.
• Design and optimize RAG pipelines with embeddings, chunking, retrieval logic, and vector search.

Skills

Databases

API Development

Cloud platforms

AI/LLM development

Education

Bachelor's degree

Tools

Azure

AWS

Docker

Kubernetes

Azure DevOps

Jira

Job description

ECPI University is seeking an experienced software engineer to support the Director of AI and Analytics in building ECPI's proprietary AI suite. The role focuses on LLM applications, RAG pipelines, vector storage, and cloud-native services using Azure and AWS.

You will design multi-platform AI applications, oversee the full development lifecycle, and deliver scalable tools for faculty, staff, and students. Robust cloud experience and AI/LLM development are essential.