LLM AI Engineer - RAG Pipelines & MCP Focus

Salvo Software LLC; United States; Hybrid; USD 120,000 - 190,000; Full time

Job summary

Salvo Software LLC is expanding its AI team and seeks a hands-on AI Developer to build and operate LLM-powered systems, including open-source models via Ollama and llama.cpp. You will own RAG pipelines and MCP integrations, connect models to internal tools, and deploy production-grade Python services.

You will collaborate across distributed teams, gain mentorship while ramping up in RAG architecture, Kafka, and MCP work, and contribute to DevOps practices with Docker, CI/CD, and cloud

Qualifications

• 3–5+ years of engineering experience with production-level Python for building services.
• Hands-on LLM integration using Ollama/llama.cpp and vector retrieval with RAG pipelines.
• Experience with cloud/infrastructure: Azure or AWS, containerization with Docker, and CI/CD automation.

Responsibilities

• Serve and operate open-source LLMs locally and on-prem.
• Build and maintain RAG pipelines and vector stores.
• Develop MCP integrations connecting LLMs to internal tools and data sources.
• Build back-end services in Python powering ML inference and AI features.
• Process structured/semi-structured data (XML, Office formats) as pipeline inputs.
• Improve model quantization and GPU tuning; consider offline deployments.
• Create CI/CD pipelines for AI services; deploy on Azure/AWS.
• Automate tasks with Python, Bash, and PowerShell.
• Troubleshoot across the stack with root-cause analysis.

Skills

Python

LLM integration

DevOps fundamentals

Root-cause analysis

Remote collaboration

Tools

Ollama

llama.cpp

Docker

Azure DevOps

GitHub Actions

GitLab CI

Kubernetes

Terraform

Apache Kafka

Python

Job description

Salvo Software LLC is expanding its AI team and seeks a hands-on AI Developer to build and operate LLM-powered systems, including open-source models via Ollama and llama.cpp. You will own RAG pipelines and MCP integrations, connect models to internal tools, and deploy production-grade Python services.

You will collaborate across distributed teams, gain mentorship while ramping up in RAG architecture, Kafka, and MCP work, and contribute to DevOps practices with Docker, CI/CD, and cloud