AI Developer

Salvo Software is currently expanding its global artificial intelligence division and is seeking a skilled AI Developer to join its remote team. This is an excellent opportunity for an engineer who is passionate about moving beyond theoretical machine learning and into the practical, high-impact world of AI production.

The company, which maintains a distributed footprint across multiple time zones, focuses on high-performance custom software and scalable engineering solutions. They are looking for a practitioner who prioritizes reliability and clean code, helping to bridge the gap between experimental LLM features and robust, deployed systems.

About the role

At the heart of this position is the development and operation of LLM-powered ecosystems. Rather than requiring you to be a researcher who builds models from scratch, Salvo Software needs an engineer who knows how to harness existing open-source technology to solve real-world business problems. You will work closely with product teams to design workflows that are not only intelligent but also scalable and secure.

While you will be deeply involved in the AI stack, strong DevOps fundamentals are essential to ensure your systems perform reliably in production. You will be expected to manage the lifecycle of these applications, from initial prototyping through to deployment on cloud infrastructure.

What you’ll do

Your daily routine will involve building the connective tissue between large language models and enterprise data. You will be responsible for:

• Operating and serving open-source LLMs using tools like Ollama and llama.cpp in various environments.
• Designing and maintaining Retrieval-Augmented Generation (RAG) pipelines, including handling vector databases, chunking strategies, and retrieval optimisation.
• Developing Model Context Protocol (MCP) integrations to give models access to internal company tools and data repositories.
• Engineering production-grade backend services using Python to support AI inference.
• Managing data ingestion pipelines that process complex formats such as XML, XSD, and standard Office documents.
• Collaborating with engineering teams to move features from sandbox environments into fully-fledged, production-ready solutions.

What they’re looking for

Salvo Software values technical maturity and a proactive approach to problem-solving. They are looking for a developer who can take ownership of their work in a remote setting, ensuring that communication remains clear across distributed teams.

Key requirements include:

• Three to five years of professional experience in software engineering, specifically with Python in production environments.
• Demonstrable experience with LLM integration, including hands-on work with vector retrieval and modern inference tools.
• Strong cloud and infrastructure knowledge, particularly with Azure or AWS, and a firm grasp of containerisation (Docker) and CI/CD automation.
• A solid understanding of DevOps practices, including Linux/Windows administration, observability tools (like Prometheus/Grafana), and secure coding standards (SOC 2 or ISO 27001 awareness is beneficial).
• The ability to learn new technologies quickly, with a growth mindset towards areas like model quantization, GGUF, and GPU/CUDA tuning.

For South African developers, roles focusing on "AI Engineering" rather than pure data science are becoming increasingly valuable. These positions typically offer competitive compensation that aligns with international remote-work standards, often benchmarking above local senior software engineering roles due to the niche requirement for LLM orchestration. As companies transition from "experimenting" with AI to "deploying" it, professionals who combine standard DevOps rigour with AI-specific pipeline knowledge are seeing significant growth in their career paths, often leading into roles like AI Architect or Lead ML Engineer.

• 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.