NVIDIA is at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Networking Research group is seeking a talented and motivated Software Engineer to spearhead the integration of autonomous AI agents across our internal and external platforms. In this high-impact role, you will architect the backbone for AI agent interaction, design scalable frameworks and SW development platforms. You will be a key player in redefining how our tools and services leverage generative AI. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you.
What you'll be doing:
Architect and build robust, scalable frameworks and APIs to integrate AI agents with NVIDIA's suite of developer tools, simulation platforms, and enterprise software.
Collaborate with research, applied AI, and product teams to understand agent capabilities and translate them into production-ready services and features.
Design and implement CI/CD pipelines and MLOps for the AI agent and SW simulation products, including testing, deployment, monitoring, and continuous improvement.
Optimize the performance, latency, and resource consumption of deployed AI agents, ensuring they operate efficiently within our compute infrastructure.
Develop internal tooling and automation to streamline the onboarding of new AI agents and enhance the observability of agent fleets.
Champion guidelines for secure and reliable agent-based systems, including data handling, access control, and interaction protocols.
Serve as a key technical resource for solving sophisticated integration issues between AI agents and target applications.
What we need to see:
BSc or above in Computer Science, Computer Engineering, or a related field, or equivalent experience.
3+ years of hands-on experience in software engineering, with a focus on backend systems, cloud services, or infrastructure.
Proven experience with AI/ML frameworks (e.g., PyTorch, TensorFlow) and a strong understanding of large language models (LLMs), transformers, and agent-based architectures (e.g., LangChain, LlamaIndex).
Proven experience in architecting, building and deploying complex integrations between AI agents and external tools, APIs, or software services.
Expert-level programming skills in Python. Experience with C++ is a strong plus.
Experience designing, building, and maintaining RESTful APIs, gRPC, and other service-to-service communication protocols.
Excellent problem-solving skills and the ability to navigate complex, ambiguous technical challenges.
Strong communication and interpersonal skills, with a proven ability to collaborate effectively across multidisciplinary teams.
Ways to stand out from the crowd:
Hands-on experience building or fine-tuning LLMs or other generative models.
Prior experience with MLOPs, and agentic infrastructure.
Contributions to open-source AI/ML projects. Experience with Infrastructure as Code (Terraform, Ansible). Prior experience in developing platforms for internal developer communities.
Knowledge of cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes, Docker), and building scalable microservices.
Familiarity with vector databases (e.g., Milvus, Pinecone) and model serving infrastructure (e.g., Triton Inference Server).
NVIDIA is home to some of the most innovative and dedicated professionals in the industry. We are committed to fostering a diverse work environment and are proud to be an equal-opportunity employer.
Skills Required
- BSc or above in Computer Science, Computer Engineering, or related field, or equivalent experience
- 3+ years hands-on software engineering experience focused on backend systems, cloud services, or infrastructure
- Proven experience with AI/ML frameworks (PyTorch, TensorFlow) and strong understanding of LLMs, transformers, and agent-based architectures (e.g., LangChain, LlamaIndex)
- Proven experience architecting, building, and deploying complex integrations between AI agents and external tools, APIs, or software services
- Expert-level programming skills in Python
- Experience with C++
- Experience designing, building, and maintaining RESTful APIs and gRPC service-to-service protocols
- Experience designing and implementing CI/CD pipelines and MLOps for agent and simulation products (testing, deployment, monitoring)
- Excellent problem-solving skills and ability to navigate complex, ambiguous technical challenges
- Strong communication and interpersonal skills; proven ability to collaborate across multidisciplinary teams
- Hands-on experience building or fine-tuning LLMs or other generative models
- Prior experience with agentic infrastructure and MLOps platforms
- Contributions to open-source AI/ML projects; Infrastructure as Code experience (Terraform, Ansible)
- Knowledge of cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes, Docker), and building scalable microservices
- Familiarity with vector databases (Milvus, Pinecone) and model serving infrastructure (Triton Inference Server)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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