1 day ago
Tel Aviv-Yafo, IsraelMid Level
Responsibilities
- Build and productionize agentic AI solutions, tools, and applications for the NVIS delivery organization.
- Develop LLM-based agents, agent workflows, orchestration logic, backend services, APIs, data pipelines, and automation features.
- Translate field, delivery, operations, and product needs into technical implementations and working software.
- Create agents and workflows that analyze project data, knowledge bases, operational systems, logs, reports, and delivery processes.
- Implement retrieval-augmented generation, context management, agent memory, function calling, evaluations, and guardrails.
- Integrate LLMs and agents with enterprise systems, project data sources, knowledge repositories, reporting tools, and operational workflows.
- Collaborate with software developers, architects, product managers, DevOps/SRE, and NVIS field teams to deliver reliable, scalable solutions.
- Contribute to code quality, testing, observability, documentation, security, CI/CD, and production support practices.
Requirements
- Bachelor of Science degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
- At least 2 years of hands-on software development experience building production applications, platforms, automation tools, or AI-based systems.
- Strong Python programming and modern backend development experience.
- Hands-on experience with LLMs, agentic workflows, tool or function calling, RAG, and AI application development.
- Experience implementing APIs, data services, workflow automation, and enterprise-system integrations.
- Experience testing, evaluating, monitoring, and handling failures in software built around nondeterministic AI systems.
- Experience with Docker, Kubernetes, Git, observability, and cloud-native development practices.
- Background with SQL and NoSQL databases, data modeling, querying, indexing, and data integration.
- Preferred experience includes agent platforms, copilots, multi-agent systems, tool-calling workflows, evaluation frameworks, MCP-style integrations, context engineering, AI safety guardrails, AI infrastructure, HPC clusters, NVIDIA DGX systems, SuperPOD, Spectrum-X, Ethernet, InfiniBand, Kubernetes, SLURM, workflow automation, Linux, networking, security, SRE, or distributed systems.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.