Senior AI Engineer

at Nvidia

USD 168,000-322,000 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 7 API @ 4 Agentic AI @ 6 CRM @ 4 Communication @ 4 GPU @ 4 GenAI Generative AI @ 6 JSON @ 7 Java @ 6 Kubernetes @ 4 LLM LangChain @ 4 Leadership @ 6 Machine Learning Observability @ 4 Python @ 7 RAG @ 4 React @ 4 SQL @ 7 Security @ 7 Vector Databases @ 4

Details

Join NVIDIA Operations' AI & Automation Supply Chain Business Transformations team to develop agentic AI at scale. This role focuses on codifying decision logic and implementing decision intelligence to deliver trusted, scalable, and innovative AI agents for Supply Chain Operations.

Responsibilities

Develop and own enterprise-grade agentic AI systems for Supply Chain use cases, including multi-agent architectures, orchestration frameworks, RAG pipelines, deployment, monitoring, and full lifecycle management.
Capture design requirements, translate requirements into user stories, perform technical design, drive end-to-end integration testing, support data setup and issue remediation during UAT, manage development team activities, and develop a hypercare support model.
Be hands-on in developing enterprise-grade agentic AI Supply Chain solutions.
Partner with Enterprise IT engineering, product, and research teams using LLMs, agentic frameworks, and NVIDIA technologies such as NeMo and AIQ.
Integrate enterprise IT and Operations data sources with industry agentic platforms, maintaining a strong focus on content security.
Drive architectural decisions across on-premises, cloud, hybrid, and containerized deployment models to deliver scalable, reliable, and efficient solutions.
Lead technical design reviews, develop technical design documentation, and follow software development principles.
Define agent autonomy boundaries, human-in-the-loop workflows, and escalation strategies for enterprise Supply Chain use cases.
Design and implement agent observability and evaluation frameworks covering latency, accuracy, cost, failure modes, and hallucination analysis.

Requirements

Bachelor's degree in Computer Science or a related field, or equivalent experience, and 8+ years of demonstrable experience in software architecture, systems design, or enterprise platform engineering.
Strong hands-on expertise in Python for building production-grade AI systems, along with experience in SQL, JSON, and backend service development. Java is a plus.
Proficiency in AI/ML systems, generative AI, or agentic AI frameworks.
Experience with LLMs, RAG architectures, and agent orchestration frameworks such as ReAct patterns, LangChain-based systems, and AutoGPT-style workflows.
Hands-on experience with vector databases, embeddings, and retrieval optimization, including indexing strategies, similarity search tuning, and relevance evaluation for production systems.
Experience designing multi-agent communication and coordination patterns, including planner/executor/critic and supervisor-agent architectures.
Experience integrating enterprise platforms such as ERP, CRM, and ITSM systems using APIs, data connectors, or custom services.
Strong technical solution design and analytical skills, including the ability to perform technical and business process modeling.
Excellent collaboration skills and the ability to influence cross-functional stakeholders and build trusted partnerships.
Ability to communicate complex architectural concepts clearly and build confidence among technical and business audiences.

Preferred Qualifications

Hands-on experience with containerized deployments, Kubernetes, and hybrid cloud/on-premises environments.
Python prototyping skills and the ability to build proof-of-concept agent workflows.
Experience with NVIDIA AI technologies such as NeMo, Guardrails, AIQ, or GPU-optimized inference stacks.
A track record of publishing technical papers, architecture patterns, or thought leadership in AI systems.
Knowledge of observability tools, telemetry dashboards, and evaluation frameworks for AI-agent performance.
Experience solving real-world problems with AI in the Supply Chain domain.

Compensation and Benefits

The expected base salary ranges are $168,000–$270,250 USD for Level 4 and $200,000–$322,000 USD for Level 5. Base salary is determined by location, experience, and other objective job-related factors. The role also includes eligibility for equity and benefits.

Applications will be accepted at least until November 6, 2026. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.