Position Overview

MangoBoost builds full-stack AI infrastructure for next-generation hyperscale AI data centers. Our work covers AI networking, next-gen GPU systems and high-performance storage, along with the software ecosystem that ties them together. Within this stack, the DPU (Data Processing Unit) is an FPGA- or SoC-based PCIe card that offloads and accelerates network and storage processing from the CPU.

Our team develops the software that runs the Platform Device, a component shared across the DPU solutions deployed in AI infrastructure. This includes:

Firmware that controls the card’s internal hardware
Discovery and initialization of the PCIe card on Embedded Linux and on x86/Arm host servers
Network interface drivers
Management functions such as health monitoring, firmware updates and diagnostics

In this role, you will develop a common evaluation framework that spans every layer from firmware to CLI tools. It will let this software be evaluated against the same criteria on DPU products built on FPGAs and SoCs from multiple vendors. Building on it, you will automatically verify the functionality, compatibility, reliability and performance of each layer and of the integration between layers. You will also work with the development teams to trace defects to their root causes, so the card runs reliably under any HW/SW combination. You should be able to build environments ranging from hardware-free emulation to automated test labs with real cards attached. You should also be able to design test code and tools that can be reused as the product line keeps growing.

Responsibilities & Opportunities

Define per-layer evaluation strategies, test items, and pass criteria for the platform software stack, from firmware to CLI tools.
Develop reusable unit, integration, and system test frameworks, along with common libraries for device control and result collection.
Build hardware-free validation environments (mocks, QEMU) for drivers, embedded Linux, and firmware.
Build test labs with real cards and automate CI regression testing across build, flashing, remote reset, testing, and log collection.
Run functional, compatibility, reliability/stress, and performance evaluations across Linux distributions, kernel versions, and hardware configurations.
Track results with environment and version history, and build reports that surface functional and performance regressions.
Reproduce defects, narrow down root causes with the hardware, firmware, and driver teams, and verify that issues don’t recur.

Required Qualifications

BS or higher in Computer Science, Electrical Engineering or a related field, or equivalent practical experience
3+ years of experience in system software development or test automation development, including industry and research projects
Hands-on experience developing test automation tools, frameworks and test code, including scripts such as Bash
Ability to develop software in Python or C/C++ on Linux, and to read C code to understand its behavior
Solid Linux system fundamentals: boot process, kernel modules, device/process/memory management, networking
Debugging skills to analyze and validate the behavior of drivers, firmware and system tools on real hardware, and to narrow down root causes based on logs and reproduction steps
Ability to clearly explain evaluation methods and results, and to read and write technical documents and handle day-to-day work discussions in English

Preferred Qualifications

Experience in functional and performance evaluation of PCIe devices such as NICs, DPUs, SmartNICs or AI accelerators, or an understanding of server PCIe card management functions (sensor monitoring, firmware updates, etc.)
Experience developing or validating device drivers or management firmware
Experience developing or validating embedded Linux/BSPs, including image builds with Yocto/OpenEmbedded, Buildroot, etc., and boot, package and update validation
Experience with emulator-based device modeling (e.g., QEMU) or building hardware-free validation environments
Experience building and operating test frameworks such as pytest and CI/CD with GitHub Actions or similar
Experience building and operating a real-hardware test lab integrated with CI (device allocation, remote power control, automatic recovery, UART/JTAG/BMC/IPMI, etc.)
Experience designing fault-injection, stress or long-duration load tests, or tracking down and reducing intermittent failures that show up across repeated runs
Experience in performance analysis and in analyzing and visualizing test result data
Active use of AI coding agents in development work

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.