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Required AI Architect- R&D and Innovation Center
Description
The AI Architect will own the technical architecture for AI-driven solutions, ensuring scalability, reliability, and alignment with business goals.
Key Responsibilities:
Design and document the architecture for generative AI solutions.
Evaluate and select appropriate models, frameworks, and infrastructure.
Define standards for data pipelines, model lifecycle management, and security.
Collaborate with engineering, data, and product teams to translate business needs into technical solutions.
Lead technical reviews and provide guidance on best practices and emerging technologies.
Ensure compliance with data privacy, security, and ethical AI guidelines.

Lead security efforts in your domains and reflect the security posture and gaps to stakeholders
Define and execute annual roadmaps to mitigate security risks and design secure architectures in diverse business units
Review and assess newer complex environments, discovering security gaps and creating security control in the form of policies and other mitigations
Develop best practices and security standards for the organization
Carry out proof of concepts for the latest security tools based on security needs and your own research
Work closely with DevOps team and development teams.

We are looking for a visionary Chief System Architect to lead the design and evolution of real-time AI infrastructures and cutting-edge vision-based systems at the edge.
This is a key executive role, reporting directly to the CEO, with broad ownership over system architecture and strategic technology development.
Responsibilities
Define and lead the architecture of our next-generation AI and real-time systems for edge deployment.
Build scalable, robust, and efficient infrastructures to support deep learning, vision, and perception models in real-world environments.
Oversee the integration of real-time computing frameworks, AI inference engines, and system-level services across heterogeneous hardware platforms.
Lead technical alignment across AI research, algorithm, hardware, and software teams to ensure seamless system design and execution.
Establish system-wide best practices for real-time performance, resource management, inter-process communication (IPC), scheduling, and fault tolerance.
Guide the selection and integration of industry-standard and proprietary real-time technologies (e.g., RTOS, ROS 2, Adaptive Autosar).
Evaluate and integrate new hardware accelerators (GPU, NPU, DSP) to optimize AI execution pipelines under strict real-time constraints.
Stay at the forefront of advancements in real-time AI, embedded vision technologies, and system design methodologies, and incorporate them into the company's technical strategy.

We are international Multi-Cloud experts, utilizing the power of the cloud for smart digital transformation. With 5 sites over 4 continents around the globe, +450 experts, +1000 customers, and +30 years of proven experience, our mission is to deliver the best Multi-Cloud service to our customers, accelerate their business and help them grow. As tech-savvies, To help our customers stay on top of their game, our teams are constantly developing new strategies and tools that will help them improve cloud performance, spending, visibility, control, and automation. Our cloud experts will make any digital transformation a quick, smart, and easy process

What You'll Do:

Realization and implementation of the architecture on the variety of technological components and services
Implementation of automations and scripts based on Infrastructure As A Code (for example: Terraform)
Implementation and implementation of protection and security solutions in the cloud
Maintaining regular interfaces with the security and cloud protection teams in the organization
Locating and implementing new technological opportunities in the cloud field
Maintaining regular interfaces with companies and organizations in the cloud field in Israel and in the community

The Enterprise Security Architecture team is looking for an Associate Director, AI Enterprise Security Architecture.
Job ID REQ-10053181
This role will contribute to the development of AI Security architectural standards, and the direction and design of architecture for a business or technical domain, while contributing to efforts to elaborate and communicate the architecture of the given domain and/or develop architectural solutions for projects and programs.
About the Role
Key responsibilities:
Oversee AI architectural activities for a specific business or technology domain, or architectural practice area, and manage the development of solution architectures for projects or programs within a business area.
Define AI security standards and direction of architecture in the specific business or technical domain, and establish best practices for protecting AI pipelines, datasets, and models.
Define and develop the logical architectural design and strategies necessary to secure the Organizations AI domain / infrastructure
Utilize architecture patterns to suggest the most adequate utilization of technical platforms in support of the holistic AI solution security architecture design.
Define, create and evolve the Architecture Governance Framework (e.g. architecture methods, practices and standards ) for AI.
Understand and advocate the principles of business and IT strategies, Be prepared to sell the Architecture process, its outcome and ongoing results, and to lead the communication, marketing or educational activities needed to ensure Enterprise Architecture success and use.
Assess the organization's AI landscape and identifying potential vulnerabilities or weaknesses including identification and evaluation of risks associated with training, deployment, and operation of AI models; keep up-to-date with the latest security threats, trends, and best practices to ensure the AI security infrastructure remains effective, and evaluate and select security tools, technologies, and products to enhance AI security.
Collaborate with IT teams to integrate security measures into all aspects of the AI platforms and LLMs related processes, working with data scientists, engineers, and DevOps teams to embed security into the AI development lifecycle, and provide guidance and support to other Engineering teams in implementing security measures and resolving security-related issues
Regularly reporting on the status of AI security measures to senior management and stakeholders.
Securing AI systems from development through deployment, including securing training data and monitoring deployed models for threats. Knowledge of AI solutions development lifecycle and environments including MLOps and related tooling (e.g. model repositories, data pipelines, deployment architectures).