AI Developer

Salvo Software; Washington (District of Columbia); Remote; USD 120,000 - 180,000; Full time

Job summary

Salvo Software LLC is building a new AI department in the United States and seeks an hands‑on AI Developer to design and operate LLM‑powered systems. You will serve open‑source models with Ollama/llama.cpp, craft RAG pipelines, and implement MCP integrations while refining ML inference services in Python.

You will collaborate with distributed teams across the US and beyond, applying DevOps practices, Docker and cloud deployments (Azure/AWS) to deploy reliable AI features and maintain system

Qualifications

• 3–5+ years engineering experience with production‑level Python for building real services, LLM inference, RAG pipelines, and automated tooling.
• Hands‑on LLM & AI integration serving models via Ollama/llama.cpp, implementing vector retrieval/RAG, and developing MCP integrations (GPU/CUDA tuning & model quantization nice to have).
• Cloud & Infrastructure expertise covering Azure/AWS deployments, Docker containerization, Linux/Windows admin, and CI/CD automation (Azure DevOps, GitHub Actions, or GitLab CI), with Terraform, Kubernetes, Kafka, or systems languages (Go, Rust, C++) as a plus.
• DevOps, Security & Operations awareness, including Git workflows, scripting (Python, Bash, PowerShell), observability tools (Prometheus/Grafana), DevSecOps, and compliance frameworks (SOC 2, ISO 27001, Zero Trust).
• Strong problem‑solving & communication with a root‑cause troubleshooting mindset, self‑directed learning, strong ownership, and seamless remote/distributed team collaboration.

Responsibilities

• Serve and operate open‑source LLMs using Ollama and llama.cpp, locally and in on‑prem environments.
• Build and maintain RAG pipelines: embeddings, vector databases, chunking strategies, and retrieval quality.
• Develop MCP (Model Context Protocol) integrations connecting LLMs to internal tools and data sources.
• Build backend services in Python that power ML inference and AI‑driven product features.
• Parse and process structured and semi‑structured data (XML/XSD, Office document formats) as pipeline inputs.
• Grow into model optimization over time: quantization (GGUF), GPU/CUDA tuning, and offline/air‑gapped deployments.

Skills

Python

LLM integration

RAG pipelines

DevOps

Docker

Azure

AWS

CI/CD

Kubernetes

Kafka

Ollama/llama.cpp

GPU/CUDA tuning

Model quantization

Terraform

Go/Rust/C++

Tools

Docker

Azure DevOps

GitHub Actions

GitLab CI

Kubernetes

Terraform

Ollama

llama.cpp

Kafka

Prometheus/Grafana

Job description

Salvo Software is a global technology company specializing in custom software development and advanced engineering solutions. With distributed teams across the US, LATAM, and India, we partner with clients to build high‑performance, scalable systems that solve complex technical challenges. Our culture values innovation, ownership, and engineering excellence. We're growing our AI department and are looking for a hands‑on AI Developer to help build it.

Role Overview

We are looking for an AI Developer to join and strengthen our AI department. Your core work will be building and operating LLM‑powered systems: serving open‑source models with Ollama and llama.cpp, building RAG pipelines, and developing MCP integrations that connect large language models to real tools and data. Solid DevOps fundamentals - Docker, CI/CD, Azure - support this work, but AI engineering is the heart of the role.

You don't need to be a deep ML researcher. What matters is production‑grade Python, strong fundamentals, and the aptitude to learn fast. You'll work closely with our engineering and product teams to take LLM‑powered features from prototype to reliably deployed systems, with mentorship available as you ramp up in areas like RAG architecture, Kafka, and advanced MCP work.

Key Responsibilities

AI / LLM Engineering (core focus)

• Serve and operate open‑source LLMs using Ollama and llama.cpp, locally and in on‑prem environments.
• Build and maintain RAG pipelines: embeddings, vector databases, chunking strategies, and retrieval quality.
• Develop MCP (Model Context Protocol) integrations connecting LLMs to internal tools and data sources.
• Build backend services in Python that power ML inference and AI‑driven product features.
• Parse and process structured and semi‑structured data (XML/XSD, Office document formats) as pipeline inputs.
• Grow into model optimization over time: quantization (GGUF), GPU/CUDA tuning, and offline/air‑gapped deployments.

DevOps & Infrastructure (supporting)

• Build and maintain CI/CD pipelines for AI services (Azure DevOps preferred; GitHub Actions / GitLab CI also used).
• Deploy AI workloads to Microsoft Azure,AWS and containerize services with Docker.
• Automate operational tasks with Python, Bash and/or PowerShell scripting.
• Troubleshoot across the stack - dig into root causes rather than patching symptoms.
• Support event‑driven architectures using Apache Kafka (producers/consumers).

Requirements

• 3–5+ years engineering experience with production‑level Python for building real services, LLM inference, RAG pipelines, and automated tooling.
• Hands‑on LLM & AI integration serving models via Ollama/llama.cpp, implementing vector retrieval/RAG, and developing MCP integrations (GPU/CUDA tuning & model quantization nice to have).
• Cloud & Infrastructure expertise covering Azure/AWS deployments, Docker containerization, Linux/Windows admin, and CI/CD automation (Azure DevOps, GitHub Actions, or GitLab CI), with Terraform, Kubernetes, Kafka, or systems languages (Go, Rust, C++) as a plus.
• DevOps, Security & Operations awareness, including Git workflows, scripting (Python, Bash, PowerShell), observability tools (Prometheus/Grafana), DevSecOps, and compliance frameworks (SOC 2, ISO 27001, Zero Trust).
• Strong problem‑solving & communication with a root‑cause troubleshooting mindset, self‑directed learning, strong ownership, and seamless remote/distributed team collaboration.