AI Developer
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Before you apply
LocationMexico
Work moderemote
Typefull-time
SeniorityMid
Experience3–5 yrs
DepartmentFirmware Development
Company size5+ people
PostedOct 5, 2026 · 1mo ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
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.
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.
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).
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.
Skills
Python
Ollama
llama.cpp
RAG
MCP
Docker
CI/CD
Azure
AWS
Git
Bash
PowerShell
Kubernetes
Terraform
Apache Kafka
Go
Rust
C++
Zig
Prometheus
Grafana
Kotlin
JVM
Linux
Windows
GPU
CUDA
Benefits
Remote work
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.