About us
MangoBoost, Inc.
Agentic AI is fundamentally reshaping the paradigm of AI infrastructure. As environments emerge where countless AI agents operate simultaneously, conventional data center architectures are reaching their limits in both performance and efficiency. In response to this shift, MangoBoost is pioneering a new approach with its full-stack AI infrastructure solution designed to innovate every layer of the AI data center.
From LLMBoost, our AI inference optimization software, to GPU and storage systems powered by our proprietary DPU architecture, and orchestration software that seamlessly integrates and manages the entire stack, MangoBoost designs and develops every layer of AI infrastructure in-house. Rather than building isolated products, we focus on eliminating system-wide bottlenecks and fundamentally addressing inefficiencies across the entire infrastructure stack.
MangoBoost’s technology minimizes data movement and coordination overhead while maximizing overall system resource utilization, enabling exceptional performance and optimized total cost of ownership (TCO) for customers. Today, our solutions are already being deployed within real-world AI infrastructure environments through global partners, validating the strength of our technology. Through these efforts, MangoBoost is establishing a new global standard for AI data centers.
Position Overview
MangoBoost is engineering the full-stack AI infrastructure driving next-generation, hyper-scale AI data centers—spanning advanced AI networking, next-gen GPU systems, high-performance storage, and the full-stack software ecosystem. The Solution Evaluation team is where breakthrough hardware meets production-scale deployment, anchored by methodology-driven system validation and high-performance systems engineering. On this team, you will build multi-node clusters, integrate PCIe-based devices such as DPUs/SmartNICs into real environments, and run hardware-software co-debugging to resolve deep system bugs alongside our HW logic design teams. This role requires a deep, full-stack understanding of modern hardware-software systems to profile complex system bottlenecks and engineer automated evaluation frameworks, providing a direct path to growing into a systems architect or technical lead.
Responsibilities & Opportunities
- Evaluate next-generation PCIe devices (AI NICs, DPUs, and storage accelerators) through real-world workload execution, characterizing system-wide performance and dynamic behavior
- Isolate complex deployment anomalies by developing advanced validation tools or high-stress injection frameworks, and collaborate directly with HW logic designers to root-cause and debug hardware-software boundary issues
- Architect, code, and operate automated performance evaluation pipelines to deploy, profile, and tune collective communication workloads across massive multi-node clusters
- Lead industry-standard benchmark initiatives (e.g., MLPerf, IO500, SPECstorage) and drive competitive analysis against leading market solutions
Required Qualifications
- BS, MS, or PhD in CS, EE, CE, or equivalent practical experience
- 2+ years of industry or academic experience in systems programming, test automation development, or software development
- Exceptional debugging, software-driven root-cause analysis, and troubleshooting skills on live, bare-metal hardware-software systems
- Solid understanding of modern data center architectures, topologies, and high-speed devices
- Strong coding proficiency (Python, C/C++, Bash, or similar) with a mindset geared toward full automation
Preferred Qualifications
- Hands-on experience scaling and managing heterogeneous GPU infrastructures (e.g., AMD GPU environments) or optimizing distributed collective communication libraries (e.g., NCCL, RCCL)
- Practical experience deploying, configuring, and optimizing large-scale RoCEv2 or InfiniBand networks and fabrics
- Deep background in high-performance networking architectures, DPU/SmartNIC technologies, or enterprise storage protocols
Notice Regarding Return of Hiring Documents
- This notice is in accordance with Article 11, Section 6 of the Fair Hiring Procedure Act, which allows job applicants, excluding the final successful candidate, to request the return of any recruitment documents they have submitted.
- Job applicants who were not selected as the final candidates in the recruitment process are entitled to request the return of the recruitment documents they submitted within 180 days of the date the employment decision is confirmed. However, this does not apply to documents submitted via the website or email, or documents voluntarily submitted by the applicant without the company’s request. If the recruitment documents are lost due to natural disasters or other reasons for which the company is not responsible, it will be considered as having been returned.
- Applicants wishing to request the return of their recruitment documents should fill out the Request for Return of Hiring Documents [Form 3 of the Enforcement Rules of the Fair Hiring Procedure Act] and submit it by email (recruiting@mangoboost.io). The documents will be sent by registered mail to the designated address within 14 days from the confirmation of submission. Please note that the cost of registered mail will be borne by the recipient.
- The company will keep the recruitment documents for 180 days following the confirmation of the employment decision. If no request for the return of documents is made within that period, the company will dispose of all recruitment documents without delay in accordance with the Personal Information Protection Act.
