Software Engineering - Distributed Agentic AI Systems

Software Engineering - Distributed Agentic AI Systems Description - This role is responsible for driving the technical design, development, and implementation of a comprehensive software stack into a closed clustering of PCs, enabling the offloading of workloads and AI inferencing along the private network. The role plays a crucial part in building technical solutions to execute hardware proof-of-concepts (POCs) for workflow tests, bridging advanced Agentic AI frameworks with underlying operating systems, edge devices, and distributed network layers. The role is responsible for technical need analysis and supporting cross-functional engineering execution while ensuring enterprise-grade application security, policy management, and container or process isolation controls.

Builds standards, designs, and automates the deployment of software. Leads the building, installation, and end-to-end integration of a complete software stack to run hardware proof-of-concepts (POCs) and workflow tests across a closed clustering of PCs. Architects and executes distributed computing strategies for workload orchestration, seamlessly managing tasks from client nodes to private servers and cloud environments. Installs, configures, and runs autonomous agents across both Windows and Linux environments, integrating agentic workflows with local and edge hardware architectures. Designs and develops solutions that protect and manage software products, application/network layers, network protocols, and data movement across private network boundaries. Implements rigorous application security and policy management frameworks, including configuring and maintaining AppArmor and SELinux security controls on Linux environments. Contributes to technology strategy and engineering roadmaps around distributed AI inference, offloading workloads, and edge device communication. Collaborates with cross-functional teams to analyze system telemetry, resource utilization, and computing bottlenecks during persistent agent simulations. Assists supervisors with project development, including documentation of features, recording of progress, and creation of testing plans for hardware-software co-design. Consults with the business to determine logical design for new business solutions according to existing distributed computing architecture and edge requirements. Identifies, recommends, and implements changes to enhance the effectiveness of engineering implementation, cluster deployment, and service strategies.

Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 7-10 years of work experience, preferably in software design and development, distributed systems architecture, systems programming, or a related field. Preferred Certifications Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) Cloud, Linux Administrator, or Network Security Certifications Knowledge & Skills Advanced English proficiency Agile Methodology Application Programming Interface (API) C++ (Experience) Computer Science DevOps HW and Driver communication in Windows (Deep knowledge) Software Engineering Machine Learning & AI Inferencing (Deep understanding of how AI inferencing works, including practical knowledge of Llama.cpp and vLLM) Agentic AI Frameworks & Tools (Experience with LangChain, LangGraph, and deploying autonomous agents) Distributed Computing & Workload Orchestration (Client-to-private server-to-cloud architectures, clustering, and network offloading) Software Engineering & Python Programming (Advanced proficiency) Operating Systems & Edge Computing (Deep operational experience in Linux and Windows environments, plus edge device integration) Application & Network Security (Network protocols, application layers, policy management, AppArmor, and SELinux