Senior Software Engineer, Platform Engineering
Nvidia
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7,129 open engineering roles across 733 companies are on ApplySarthi right now, most of them in Bengaluru (364), Hyderabad (129), Mumbai (54).
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What engineering roles keep asking for: Python (22%), AWS (21%), Observability (14%), System design (13%), CI/CD (12%) — counted across their open postings here.
Software Engineer jobs in the United States · Remote Software Engineer jobs · Docker jobs · Generative AI jobs · Kubernetes jobs · LLMs jobs
Nvidia has 3,820 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for engineering roles keep coming back to Python, AWS, Observability, System design. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with RAG? Tell me one thing you learned the hard way.
- Tell me about an outage you handled. What did you learn from it?
- How do you decide what to monitor, and what should wake someone up at night?
- How would you cut the cloud bill of a system without hurting it?
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Practise the Senior Software Engineer, Platform Engineering at Nvidia interview free →NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is looking to hire a deeply technical, creative, and hands-on Senior Full- Stack Software Engineer to build the next generation AI platforms and products that improve business efficiency and productivity. This engineer is expected to be familiar with concepts of RAG, agentic AI to be able to build AI products using SOTA agentic paradigms, third party platforms and open-source repos. As a key leader in our technology team, you will play a pivotal role in shaping the architecture, development, and scaling of our software systems. This role will give an opportunity to collaborate with Cloud, AI/ML & Generative AI workforce in a multifaceted and agile working environment, while meeting the immediate and evolving needs of our business. What You Will Be Doing: Hands-on experience with test automation, production testing, and automation frameworks Solid understanding of Linux, embedded systems, firmware, and hardware/software integration Deep knowledge of IT Service Management (ITSM) and ServiceNow (HR, Security, Finance modules preferred) Collaborate with cross-functional teams to deliver end-to-end intelligent experiences across applications Integrate agents with enterprise data sources, APIs, and internal microservices to enable real-world actions Architect and build agentic AI systems that leverage LLMs for reasoning, planning, and tool orchestration across enterprise workflows Develop scalable platforms for retrieval-augmented generation (RAG), long-term memory, and contextual reasoning Build reusable infrastructure for agent orchestration, tool integration, evaluation, and observability What We Need to See: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience) 8+ years of experience building large-scale distributed systems and cloud-native applications (Python preferred) Strong experience designing and deploying LLM-powered systems, including RAG, tool use, and agent-based architectures Deep understanding of agentic AI paradigms (planning, memory, tool invocation, multi-step reasoning) Experience with agent frameworks and orchestration tools (e.g., LangChain or similar) Proven ability to design systems with high reliability, scalability, and performance Hands-on experience deploying applications in Kubernetes environments Experience building systems in cloud and hybrid environments Strong programming skills across multiple languages and modern software stacks Proven track record leading complex technical initiatives and mentoring high-performing teams Ways to stand out from the crowd: Experience enhancing enterprise efficiency and employee experience through the effective use of Generative AI based solutions. Fascinated by unique and difficult problems - resilient and persistent in the pursuit of solutions. Experience with Cloud Platforms, experience with Kubernetes and Docker. Self-motivation and a drive to get things to “done”. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and passionate people on the planet working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Listed on workday · posted 2026-11-05. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.