AI Developer

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.