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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. Responsibilities 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. Education & Experience 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 controls) Core AI/Data Paradigms (Retrieval-Augmented Generation [RAG], Model Context Protocol [MCP], and prompt engineering) Systems Programming & LLM Fine-tuning (Nice to have) Cross-Org Skills Effective Communication and Cross-Organizational Collaboration Results Orientation and Learning Agility Digital Fluency and Customer Centricity Agile Methodology & DevOps Alignment Impact & Scope Impacts function and leads and/or provides expertise to functional project teams, driving architectural decisions for closed PC clustering, edge deployment, and private network AI offloading initiatives. Complexity Works on complex problems where analysis of distributed systems, multi-node clustering, AI runtimes, and low-level security controls requires an in-depth evaluation of multiple hardware and software factors. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Job - Software Schedule - Full time Shift - No shift premium (Brazil) Travel - No Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “ Know Your Rights: Workplace Discrimination is Illegal "
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.