AI Engineer

• Build agentic workflows, including loops, graphs, and multi-step pipelines, for hardware network simulation and analysis
• Engineer workflow context from simulation models, specifications, design documents, and source code
• Collaborate with network architects to understand workflows and translate them into agent workflows
• Optimize simulation tooling runtime performance, including execution time, compute cost, and end-to-end latency
• Define evaluation and regression testing for agent workflows
• Build observability across agent runs, including actions, failures, and causes
• Champion secure and reliable agent workflow guidelines covering data handling, access control, and interaction boundaries
• Solve sophisticated integration issues between agents and internal tooling

Senior AI Engineer – Network Architecture

• Design, build, and deploy AI agents that automate and augment high-value workflows across business functions.
• Own the end-to-end agent stack, including tool use, memory management, multi-step planning, human-in-the-loop escalation patterns, guardrails, and audit trails.
• Define agent evaluation frameworks measuring task completion, accuracy, hallucination rates, latency, and business impact.
• Iterate on agent behavior using real usage data and stakeholder feedback.
• Implement integrations allowing agents to take automated actions on behalf of users.
• Collaborate with engineering teams to design, build, and maintain production pipelines.

• Identify high-value opportunities for AI across the go-to-market lifecycle
• Design and ship AI agents, automations, and AI-powered workflows for prospecting, enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence, and expansion
• Turn internal prototypes into reliable production services used across the organization
• Collaborate with Engineering and DevOps to ensure solutions are secure, maintainable, and scalable
• Define where AI can act independently and where humans remain in the loop
• Build evaluation, monitoring, permissions, and auditability for agents interacting with commercial systems and data
• Work across CRM, GTM tools, and data warehouse systems to improve data connectivity, structure, and availability
• Measure business impact through cycle times, data quality, productivity, conversion, and time returned to teams
• Communicate AI impact clearly to the business
• Create patterns, tooling, and standards that enable others to build safely and effectively
• Help the organization discover, trust, and use AI capabilities
• Work across Sales, Solutions, Customer Success, Marketing, and Revenue Operations

GTM AI Engineer

• Design, build, and evolve AI agents and agentic workflows that are core to Duve’s product
• Develop production-grade AI-powered features and integrate them into the existing platform
• Take ownership of complex technical challenges from problem understanding and solution design through implementation and delivery
• Build reliable and scalable software systems supporting AI capabilities
• Evaluate new AI technologies and approaches and identify opportunities to apply them to product and business challenges
• Collaborate with Product and Engineering to turn ideas and customer needs into high-quality technical solutions
• Contribute to technical and architectural decisions across the AI team
• Maintain high engineering standards through clean code, testing, code reviews, and knowledge sharing

Senior Software Engineer – AI Agents

• Design and maintain a LangGraph-based Agent Harness optimized for online and offline/on-premise deployment
• Use hybrid LLM and deterministic layers to balance speed, memory, and costs
• Own the complete evaluation lifecycle, including datasets, benchmarking frameworks, and automated regression testing
• Ensure output accuracy through evaluation and regression testing
• Standardize tool-calling interfaces for forensic engines
• Collaborate with researchers to operationalize AI models into Cellebrite's products
• Build, evaluate, and iterate on AI and agentic solutions across the software lifecycle, from rapid prototypes and POCs to production-grade systems
• Implement solid design, flexible implementation, strong telemetry, and production feedback loops

• Translate business and product needs into well-defined problems, research plans, and technical designs
• Own AI capabilities end to end, from initial exploration through production deployment and ongoing improvement
• Develop and improve core algorithms
• Build production-grade AI agents for performance marketing, market research, and auto-ML
• Turn research into maintainable software, including reusable modules, data pipelines, and services with clear interfaces
• Implement automated tests and robust deployment practices
• Monitor system behavior and investigate failure cases in production
• Continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow
• Choose appropriate approaches across statistical methods, classical machine learning, and LLM-based systems
• Balance research depth, delivery speed, and operational complexity
• Partner with product and engineering to shape priorities and lead technical initiatives
• Review designs and code
• Mentor teammates

Senior Applied AI Engineer

• Design, develop, and deploy LLM-based and Agentic Systems for production environments
• Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems
• Develop backend services and AI solutions using Python
• Work hands-on with agentic frameworks such as LangGraph, CrewAI, or similar/custom frameworks
• Deploy and operate AI systems in cloud environments
• Troubleshoot complex system issues and improve observability, reliability, and performance
• Collaborate with development, DevOps, security, and other technical teams

• Lead the AI team and own its technical direction, roadmap, and execution
• Drive AI/ML initiatives from concept and prototyping through production deployment and ongoing optimization
• Define clear success metrics and ensure AI solutions deliver measurable product and business impact
• Lead architecture and technical decision-making around AI models, platforms, tools, and data
• Build and grow a multidisciplinary team, including recruitment, mentoring, performance management, and career development
• Establish engineering practices around evaluation, scalability, reliability, monitoring, and model lifecycle management
• Collaborate with Product Management, Systems Engineering, and R&D teams across Israel, India, and the US
• Partner with RAN and domain experts to identify opportunities for AI to improve network performance, automation, and operational efficiency
• Support customer-facing discussions, trials, and proofs of concept where relevant

AI Engineer jobs in Israel

Senior AI Engineer – Network Architecture

AI Engineer

GTM AI Engineer

Senior Software Engineer – AI Agents

AI Engineer

Senior Applied AI Engineer

AI Engineer

AI Engineering Team Manager