Senior AI Engineer
About The Position
The Senior AI Engineer joins NVIDIA Operations’ AI & Automation Supply Chain Business Transformations team to develop agentic AI capabilities for Supply Chain Operations. The role implements decision logic and decision intelligence so that AI agents deliver trusted, scalable, and innovative value. The engineer develops and owns enterprise-grade agentic AI systems across their full lifecycle, from architecture and implementation through deployment, monitoring, integration, and support. The position works with enterprise IT engineering, product, and research teams, using LLMs, agentic frameworks, and NVIDIA technologies such as NeMo and AIQ. It also helps define agent autonomy, human oversight, escalation, and evaluation practices for enterprise supply chain applications.
Requirements
- Bachelor’s degree in Computer Science or a related field, or equivalent experience.
- 12+ 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.
- Experience with SQL, JSON, and backend service development; Java is a plus.
- At least 2 years as a Palantir AI Foundry and AIP platform Forward Deployment Engineer.
- 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, such as planner/executor/critic and supervisor agents.
- Experience integrating enterprise platforms such as ERP, CRM, and ITSM with APIs, data connectors, or custom services.
- Strong technical solution design and analytical skills, and ability to perform technical and business process modeling.
- Excellent collaboration skills, ability to influence cross-functional stakeholders and build trusted partnerships, and ability to communicate complex architectural concepts clearly to technical and business audiences.
Nice To Haves
- Hands-on experience with containerized deployments, Kubernetes, and hybrid cloud/on-premises environments.
- Python prototyping skills and ability to build proof-of-concept agent workflows.
- Experience with NVIDIA AI technologies such as NeMo, Guardrails, AIQ, or GPU-optimized inference stacks.
- 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.
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 them 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.
- Implement enterprise-grade agentic AI Supply Chain solutions hands-on.
- Partner with Enterprise IT engineering, product, and research teams while using LLMs, agentic frameworks, and NVIDIA NeMo and AIQ technologies.
- Ensure integration with enterprise IT and Operations data sources and agentic platforms, with 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 code 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.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
