AI Engineer

NSO Group · herzliya

As an AI Engineer, you will : Play a central role in advancing AI capabilities across the company and turning emerging AI technologies into practical, production-ready solutions Research and evaluate new AI technologies, identify valuable use cases and develop solutions that improve internal workflows, existing products and enable new AI-powered capabilities Lead AI solutions end to end, from research and proof of concept to design, development and production Collaborate closely with development, product and business teams to integrate AI models, agents, data and reusable AI services into existing systems Design and develop RAG, knowledge systems, AI agents and multi-agent workflows Evaluate and benchmark AI models and solutions, balancing quality, accuracy, latency, throughput and cost Find creative and practical solutions to complex technical and business challenges and help expand the company’s internal AI ecosystem If you have : At least 3 years of experience in software engineering, machine learning engineering, applied AI or a related technical role Strong Python programming skills and experience building production-grade software, APIs and microservices Hands-on experience developing AI-powered applications and taking them from proof of concept to production Strong understanding of LLMs and transformer architectures Experience with RAG, embeddings and vector databases Experience in developing AI agents, tool-using workflows, MCP integrations or similar technologies Experience in evaluating and benchmarking AI models and solutions Familiarity with model-serving technologies such as vLLM, LiteLLM, SGLang, TGI or Triton Working knowledge of Docker, Kubernetes, Helm, Linux, Git, CI/CD and GitOps It would be great if you also have : Experience with PyTorch, Hugging Face Transformers or similar frameworks Experience with fine-tuning techniques such as LoRA, QLoRA, SFT, preference optimization or distillation Experience with GraphRAG, knowledge graphs, code graphs or other graph-based AI systems Experience optimizing model inference through quantization, batching, caching, parallelism or GPU-aware deployment Experience with multimodal models, synthetic data generation or AI model evaluation Experience delivering AI solutions in security-sensitive, regulated, on-premises or disconnected environments B.Sc. in Computer Science or equivalent experience

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