Software Engineering - Distributed Agentic AI Systems (AI)

Location: Porto Alegre, Rio Grande do Sul, Brazil

Company

hirify.global develops hardware and software solutions, including distributed computing and AI systems.

What you will do

• Design, develop, and automate deployment of a complete software stack for closed PC clusters, hardware proof-of-concepts, and workflow testing.
• Architect distributed computing strategies for workload orchestration across client nodes, private servers, and cloud environments.
• Install and configure autonomous agents across Windows and Linux, integrating agentic workflows with local and edge hardware.
• Develop application and network-layer solutions for secure software, policy management, data movement, and process or container isolation.
• Analyze telemetry, resource utilization, and bottlenecks during persistent agent simulations.
• Contribute to technology strategy, engineering roadmaps, documentation, and testing plans for distributed AI inference and edge communication.

Requirements

• 7–10 years of experience in software design and development, distributed systems architecture, systems programming, or a related field.
• Four-year or graduate degree in Computer Science, Information Technology, Software Engineering, or a related discipline, or equivalent experience.
• Advanced proficiency in Python and experience with C++.
• Deep knowledge of Windows hardware and driver communication, plus operational experience with Linux, Windows, and edge devices.
• Practical understanding of AI inference and agentic AI frameworks, including Llama.cpp, vLLM, LangChain, and LangGraph.
• Knowledge of distributed computing, workload orchestration, API design, network protocols, application security, AppArmor, and SELinux.

Nice to have

• Experience with systems programming and LLM fine-tuning.
• Certifications in programming languages, cloud technologies, Linux administration, or network security.

Culture & Benefits

• Full-time employment with cross-functional and cross-organizational collaboration.
• Work aligned with Agile methodology and DevOps practices.
• No travel required.
• Projects combine hardware-software co-design, edge deployment, private-network AI offloading, and distributed systems architecture.