לוח משרות דרושים הייטק AI  ברעננה

A new type of finance role designed for an AI-driven organization. You will combine strong FP&A fundamentals with curiosity for GenAI tools, modern analytics, and SaaS monetization. Working closely with AI leaders, product teams, and business stakeholders, you will help translate innovation into financial insights while contributing to core financial execution.

What will your job look like?
Support planning, forecasting, and performance analysis for Data & GenAI initiatives
Build financial models for AI solutions, SaaS offerings, and data-driven business cases
Analyze monetization approaches for GenAI-driven capabilities and internal transformation programs
Design and track KPIs measuring efficiency, productivity, and value from AI adoption
Partner closely with product, engineering, and AI leaders to translate roadmaps into financial narratives
Use GenAI and analytics tools to streamline reporting and improve decision-making workflows
Maintain ownership of core FP&A deliverables while supporting strategic decision-making

We are seeking a highly skilled and visionary Lead Data Scientist with deep expertise in Generative AI to lead high-impact initiatives at the frontier of AI innovation. This role requires a unique blend of advanced technical skills, domain specialization, leadership ability, and a passion for delivering real-world impact. You will guide a small team of talented data scientists and work collaboratively across engineering and product teams to design, build, and deploy intelligent, domain-specific multi-agent systems.

What will your job look like?
Lead the design of complex, domain-specialized multi-agent Generative AI systems.
Provide technical mentorship and leadership to a team of 3-4 data scientists.
Drive hands-on research and rapid prototyping in areas including LLM fine-tuning, prompt engineering, agentic workflows, and self-improving systems.
Collaborate with product managers, engineers, and domain experts to identify opportunities and deliver AI-driven features and products.
Evaluate and integrate state-of-the-art models and tools from the GenAI ecosystem, including open-source and proprietary solutions.
Translate research outcomes into actionable product features and influence AI strategy and roadmap.
Maintain high standards for scientific rigor and data integrity throughout the development lifecycle.

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.

Lead and mentor a team of software engineers developing Sensing AI SDK. Architect and implement high-performance sensing SW components for AI, vision, Audio and voice optimized for vectorize SIMD execution. Collaborate with compiler and DevOps teams to ensure efficient development and deployment. Drive technical excellence through code reviews, design discussions, and continuous improvement. Own the SDK roadmap, planning, and delivery cycles. Engage with customers to enable successful pre-sale processes, support integration and gather feedback.

We are looking for an AI & Automation Engineer to design, build, and enable enterprise AI infrastructure and automation solutions.
This role focuses on AI architecture, workflow automation across IT and business applications, and monitoring, governance, and cost management of AI tools and agents.
You will work at the intersection of AI platforms, IT operations, and business automation, enabling scalable, secure, and cost-effective AI adoption across the organization.
Responsibilities:
Select and integrate AI tools, frameworks, and platforms aligned with enterprise IT standards.
Ensure scalability, security, reliability, and compliance of AI infrastructure.
Enable AI solutions from concept to production, including:
AI-powered IT tools
AI agents and copilots
AI services integrated into business applications
Collaborate with IT, DevOps, Security, and Business teams to deploy AI solutions smoothly.
Build reusable AI enablement patterns, templates, and best practices.
Automation of Workflows
Design and implement automation of IT and business workflows using AI and orchestration tools.
Integrate AI agents into:
IT operations (ITSM, monitoring, incident response)
Business applications and internal systems
Improve efficiency, reliability, and user experience through intelligent automation.
AI Monitoring, Usage & Financial Governance
Define and implement monitoring for AI systems, including:
Usage tracking
Performance and reliability
Model and agent behavior
Track and analyze financial usage and cost of AI tools, APIs, and platforms.
Establish governance frameworks for responsible and controlled AI usage.