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About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. About the Role Develop a comprehensive AI reference application and maintain internal AI services to accelerate real-world deployment of RNGDs. Key Responsibilities Develop high-impact AI applications and technical resources to enable the success of the global developer community. Develop enterprise-focused, high-quality reference applications and sample code that enable developers to effectively understand and utilize FuriosaAI’s SW stack and integrations. Drive end-to-end application enablement such as RAG systems, agentic systems, and RL inference engines on FuriosaAI accelerators, creating reproducible guides and reference implementations. Evaluate applications against real-world scenarios to validate performance, reliability, and usability of RNGD deployments. Support live application demos and collaborate with the global developer community through GitHub and open-source channels to improve real-world usability. Minimum Qualifications BS in Artificial Intelligence, Computer Science, Electrical Engineering, or a related field. Experience in full-stack (frontend and backend) development of AI services. Experience collaborating across engineering, product, and design teams to align software development with product requirements. Preferred Qualifications MS or PhD in Artificial Intelligence, Computer Science, Electrical Engineering, or a related field. Experience in developing and maintaining AI products, including running A/B tests and operating services under high traffic. Experience in open-source projects on AI applications such as agentic systems, RAG, or multimodal pipelines. Contact recruit@furiosa.ai
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.