3 days ago
Tel Aviv-Yafo, Israel or Ra‘ananna, IsraelSenior
Responsibilities
- Compose, build, and productionize agentic AI solutions, tools, and applications for the NVIS delivery organization.
- Develop LLM-based agents, orchestration logic, backend services, APIs, data pipelines, and automation features for NVIS Central.
- Translate field, delivery, operations, and product needs into technical builds, agent workflows, and production software.
- Build agents and workflows that reason across 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 internal systems, project data sources, knowledge repositories, reporting tools, and operational workflows.
- Collaborate with software developers, architects, product managers, DevOps/SRE, and field teams to deliver reliable and scalable solutions.
- Contribute to engineering guidelines covering code quality, testing, CI/CD, observability, documentation, security, and production support.
Requirements
- B.Sc. degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field.
- At least 5 years of hands-on software development experience building production applications, platforms, automation tools, or AI-based systems.
- Strong programming experience with Python and modern backend development.
- Hands-on experience with LLMs, agentic workflows, tool or function calling, retrieval-augmented generation, and AI application development.
- Experience building RESTful APIs, data services, workflow automation, and enterprise-system integrations.
- Experience testing, evaluating, monitoring, and handling failures in software built around non-deterministic AI systems.
- Experience with Docker, Kubernetes, CI/CD, Git, observability, and cloud-native development practices.
- Background with SQL and NoSQL databases, data modeling, querying, indexing, and data integration.
- Preferred experience with agent platforms, copilots, multi-agent systems, tool-calling workflows, evaluation frameworks, or MCP-style integrations.
- Preferred understanding of context engineering, retrieval quality, version management, agent planning, human-in-the-loop workflows, and AI safety guardrails.
- Preferred experience with AI infrastructure, HPC clusters, NVIDIA DGX systems, SuperPOD, Spectrum-X, Ethernet, InfiniBand, Kubernetes, or SLURM.
- Strong Linux, networking, security, SRE, or distributed systems background is advantageous.
Categories
AI ApplicationsSolutions Engineering
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.