AI Developer

Salvo Software

. Serve and operate open-source LLMs using Ollama and llama.cpp locally and in on-premises environments .

Posted 11/6/2026full-timeRemote • Mexico, United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining LLMs and RAG pipelines, with strong capabilities in Python backend development, cloud deployments on Azure and AWS, and CI/CD automation. Proficient in troubleshooting and optimizing AI services while collaborating effectively with engineering and product teams.

Highest-signal resume keywords

Production-Level Python DevelopmentLLM Integration Using Ollama/Llama.cppCloud Deployment on Azure/AWSCI/CD Automation with Azure DevOpsTroubleshooting and Root-Cause Analysis

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Hard Skills

PythonLLM InferenceRAG PipelinesMCP IntegrationsDockerGPU/CUDA TuningModel QuantizationBash ScriptingPowerShell ScriptingEvent-Driven Architecture

Soft Skills

Problem-SolvingCommunicationSelf-Directed LearningOwnershipCollaboration

Tools & Technologies

Microsoft AzureAWSApache KafkaPrometheusGrafanaTerraformKubernetesGitHub ActionsGitLab CIDevSecOps

Certifications & Qualifications

SOC 2ISO 27001

Industry Keywords

DevOpsCompliance FrameworksZero TrustLinux AdministrationWindows Administration

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDockerGrafanaKafkaKubernetesLinuxPrometheusPythonRustTerraformC++Go

About the role

Key responsibilities & impact

Serve and operate open-source LLMs using Ollama and llama.cpp locally and in on-premises environments
Build and maintain RAG pipelines involving embeddings, vector databases, chunking strategies, and retrieval quality
Develop MCP integrations connecting LLMs to internal tools and data sources
Build Python backend services for ML inference and AI-driven product features
Parse and process structured and semi-structured data, including XML/XSD and Office document formats
Grow into model optimization, including GGUF quantization, GPU/CUDA tuning, and offline/air-gapped deployments
Build and maintain CI/CD pipelines for AI services
Deploy AI workloads to Microsoft Azure and AWS and containerize services with Docker
Automate operational tasks with Python, Bash, and/or PowerShell
Troubleshoot across the stack and identify root causes
Support event-driven architectures using Apache Kafka producers and consumers
Work with engineering and product teams to take LLM-powered features from prototype to reliably deployed systems

Requirements

What you’ll need

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