AI Developer

Salvo Software LLC; México; Híbrido; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Salvo Software LLC is expanding its AI department and seeks a hands-on AI Developer to build and operate LLM-powered systems. You will work across production-grade Python backends, open-source LLMs via Ollama/llama.cpp, and RAG pipelines, with strong emphasis on DevOps and cloud deployments.

You will collaborate with engineering and product teams to move from prototype to reliable, scalable solutions, while mentoring in areas like MCP work, Kafka, and model optimization.

Formación

• Production-level Python engineering for real services and pipelines
• Hands-on experience serving LLMs with Ollama and/or llama.cpp
• 3–5 years across backend, ML engineering, DevOps, or infrastructure
• Working knowledge of Docker and Linux fundamentals
• Experience with Microsoft Azure and AWS cloud deployments
• Practical experience building and maintaining CI/CD pipelines (Azure DevOps preferred; GitHub Actions/GitLab CI relevant)
• Scripting in Python, Bash and/or PowerShell
• Strong Git fundamentals and disciplined workflow
• Troubleshooting mindset with root-cause analysis
• Fast learner with ability to pick up new tools quickly
• Good communication and collaboration in a remote, distributed team
• GPU/CUDA troubleshooting experience

Responsabilidades

• AI/LLM Engineering: serve/open-source LLMs with Ollama/llama.cpp locally and on-prem
• Build and maintain RAG pipelines: embeddings, vector DBs, chunking, retrieval quality
• Develop MCP integrations linking LLMs to internal tools and data sources
• Build Python backend services powering ML inference and AI features
• Parse and process structured/semi-structured data (XML/XSD, Office formats) as pipeline inputs
• Grow into model optimization (quantization, GPU/CUDA tuning, offline/air-gapped deployments)
• DevOps & Infrastructure: maintain CI/CD pipelines (Azure DevOps preferred; GitHub Actions/GitLab CI)
• Deploy AI workloads to Azure/AWS and containerize services with Docker
• Automate tasks with Python, Bash, PowerShell
• Troubleshoot across the stack with root-cause focus
• Support event-driven architectures using Apache Kafka

Conocimientos

Python

Git

Linux

Cloud

Herramientas

Docker

Kubernetes

Terraform

Azure

AWS

CI/CD pipelines

Descripción del empleo

About Salvo Software

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 languange 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

Required

• Production-level Python - real services and pipelines, not just scripts.
• Hands-on experience serving LLMs with Ollama and/or llama.cpp.
• 3-5 years of hands-on experience across backend, ML engineering, DevOps, or infrastructure.
• Working knowledge of Docker and Linux fundamentals.
• Experience with Microsoft Azure, AWS and cloud-based deployments.
• Practical experience building and maintaining CI/CD pipelines (Azure DevOps strongly preferred; GitHub Actions / GitLab CI also relevant).
• Comfortable scripting in Python, Bash and/or PowerShell.
• Strong Git fundamentals and branching/workflow discipline.
• A troubleshooting mindset - able to work through ambiguity and dig into root causes.
• Fast learner with genuine aptitude and willingness to pick up new tools quickly.
• Good communication and collaboration skills; comfortable in a remote, distributed team.
• GPU/CUDA troubleshooting experience.

Should Have (can ramp up with mentorship)

• RAG concepts: vector databases, embeddings, chunking strategies.
• Advanced MCP (Model Context Protocol) knowledge.
• Kubernetes (kubectl basics).
• Infrastructure as code with Terraform.
• Apache Kafka fundamentals (producer/consumer patterns).

Nice to Have

• A systems language: Go, Rust, C++, or Zig.
• llama.cpp at a deeper level - building and quantizing models.
• Observability tooling (Prometheus/Grafana) and SRE practices.
• Exposure to security and compliance frameworks (SOC 2, ISO 27001, Zero Trust).
• Familiarity with DevSecOps practices and secure pipeline design.
• Experience deploying Kotlin (or other JVM-based) applications.
• Linux and Windows systems administration background.

Soft Skills

• Can explain why something broke, not just that it did.
• Comfortable saying "I don't know - I'll find out."
• Self-directed learner (side projects, home lab, open-source contributions).
• Takes feedback well and asks good questions.
• Strong ownership and problem-solving ability across time zones.