AI Application Developer at NVIDIA

Shanghai, China

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

BS or MS in Computer Science, Electrical/Computer Engineering, or a related field
2–3 years of experience building AI applications, with at least 1 year focused on developing LLM-based agents (e.g., tool use, function calling, ReAct-style reasoning, RAG integration)
Strong programming skills in Python and one of C++, JavaScript, or TypeScript
Experience with an agent framework such as LangChain Agents/LangGraph, AutoGen, CrewAI, Semantic Kernel, or Haystack Agents
Proficiency in creating custom tools/functions, integrating external APIs, and working with async workflows and retries
Practical experience with privacy, responsible AI practices, prompt engineering, and content filtering
Familiarity with PyTorch or TensorFlow, REST/gRPC, Docker, cloud platforms (AWS, Azure, or GCP), and databases (SQL/NoSQL, vector DBs)

Responsibilities

Design, implement, and deploy AI-powered features using LLMs, including autonomous and multi-agent workflows
Build agent toolchains, including planning, tool/function calling, memory management, RAG integration, and enterprise API connectivity
Enhance agent frameworks with custom planners, routers, concurrency control, state management, and retry mechanisms
Develop evaluation and observability systems to monitor agent performance (success rates, tool-call accuracy, latency, cost, traces)
Implement safety and compliance measures, including content filtering, PII handling, and policy enforcement using guardrail frameworks
Optimize inference pipelines for GPU performance, latency, and cost; deploy via microservices and APIs
Manage CI/CD, containerization, and deployment; maintain monitoring, logging, and alerting; and produce clear documentation

Skills

Key technologies and capabilities for this role

PythonC++JavaScriptTypeScriptLangChainLangGraphAutoGenCrewAISemantic KernelHaystackRAGPyTorchTensorFlowCI/CDcontainerization

Questions & Answers

Common questions about this position

What experience is required for the AI Application Developer role?

A BS or MS in Computer Science, Electrical/Computer Engineering, or related field is required, along with 2–3 years of experience building AI applications and at least 1 year focused on LLM-based agents. Strong programming skills in Python and one of C++, JavaScript, or TypeScript are needed, plus experience with agent frameworks like LangChain Agents/LangGraph, AutoGen, CrewAI, Semantic Kernel, or Haystack Agents.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What skills will help me stand out as a candidate?

Experience customizing agent frameworks, expertise in multi-agent systems or workflow orchestration, knowledge of evaluation and guardrail systems, GPU inference optimization with tools like NVIDIA Triton or TensorRT, and skills in retrieval efficiency or cost-aware inference will make you stand out.

What technical tools and frameworks should I be familiar with?

Familiarity with PyTorch or TensorFlow, REST/gRPC, Docker, cloud platforms like AWS, Azure, or GCP, and databases including SQL/NoSQL and vector DBs is required. Proficiency in creating custom tools/functions, integrating external APIs, async workflows, retries, privacy practices, responsible AI, prompt engineering, and content filtering is also needed.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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