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. Within this mission, the RDMA and AI Networking team builds the RDMA NIC for ultra-fast, high-efficiency communication in scale-out AI systems. Performance and validation engineers own the final validation of every NIC release before it reaches customers, and make sure customers get the NIC's full performance on large-scale AI and storage workloads. In this role, you will build test and benchmark automation, and analyze and tune performance across the entire system. You will also work with the driver and hardware teams to resolve functional and performance problems found before and after delivery.

Responsibilities & Opportunities

Own release validation of MangoBoost's RoCEv2 NIC
Architect, code, and operate automated validation pipelines and stress-injection frameworks on multi-node clusters
Identify functional failures and performance regressions, and isolate them to the hardware, driver, or workload layer
Profile state-of-the-art AI and storage workloads on the NIC and analyze bottlenecks from the application down to the hardware
Lead industry-standard benchmark initiatives and drive competitive analysis against competing 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, or performance engineering
Strong coding skills (Python, C/C++, Bash, or similar) with a focus on automation
Strong failure triage and performance analysis skills spanning user space, kernel, and hardware interactions
Solid understanding of modern data center architectures, topologies, and high-speed devices

Preferred Qualifications

Background in RDMA, DPU/SmartNIC, or high-performance networking
Experience with GPU clusters and AI training/inference workloads
Experience with high-performance storage (NVMe-oF, SPDK, or distributed storage)
Experience building test infrastructure or cluster tooling (CI, Kubernetes, containers)

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.

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.