Data & AI Manager jobs in Israel

Description About AllCloud AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation. AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth. AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io About the Role We are seeking a visionary and hands-on AI and Data Science Team Lead to head our advanced analytics and AI engineering group. Over the past 7 years, our data infrastructure and customer needs have evolved from foundational data engineering and cloud migrations to cutting-edge Generative AI and Machine Learning solutions. You will lead a high-performing team of AI Engineers and Data Scientists, taking ownership of the technical direction, architecture, and deployment of production-grade AI systems on AWS. The ideal candidate combines a solid foundational background in complex data architecture with state-of-the-art expertise in Gen AI, RAG pipelines, graph-based reasoning, and Enterprise MLOps. You will work closely with enterprise customers across various sectors (manufacturing, banking, healthcare, and high-tech) to translate business constraints into scalable architectures and ship systems that deliver measurable business impact. Responsibilities • Team Leadership: Recruit, mentor, and manage a team of Data Scientists and AI Engineers, driving engineering excellence, technical direction, and best practices. • System Architecture & Gen AI: Design and deploy end-to-end AI systems, including large-scale Retrieval-Augmented Generation (RAG) pipelines for technical documentation, Text-to-SQL GenBI agents, and advanced AI document processing systems (OCR, semantic extraction). • Enterprise MLOps: Design and deliver secure, enterprise-grade MLOps platforms on AWS (including CI/CD pipelines, feature stores, and monitoring) to dramatically reduce model deployment times. • Advanced Data Modeling: Utilize graph embeddings (e.g., Neo4j) and build graph-based AI agents to uncover hidden behavioral patterns, improving LLM reasoning while optimizing token costs and latency. • Customer & Stakeholder Collaboration: Work directly with enterprise customers to understand business constraints, define architectural standards, and implement governance guardrails and validation layers for safe enterprise adoption and data protection. • Hands-On Execution: Operate dynamically in both startup and enterprise contexts, balancing the need to ship value quickly with maintaining strict production rigor. Requirements • Experience: 7+ years of proven experience designing, deploying, and managing production-grade Machine Learning and AI systems (with a strong foundation in data engineering and scalable pipelines). • Leadership: Demonstrated experience leading, managing, and mentoring data science or AI engineering teams. • Cloud & Infrastructure: Deep architectural expertise in the Amazon Web Services (AWS) ecosystem, with a track record of deploying large-scale solutions. Experience defining architectural standards to achieve milestones like the AWS ML Competency is a significant advantage. • Gen AI & Search: Extensive hands-on experience with Large Language Models (LLMs), deep learning frameworks, domain-specific prompting, and vector search/Elasticsearch. • Graph Technologies: Strong background in modeling complex data structures using Graph Databases (e.g., Neo4j) to build scalable pipelines for high-volume data. • Education: M.S. (or equivalent) in Engineering, Mathematics, Computer Science, or a related quantitative field. • Communication: Excellent interpersonal skills with the ability to lead customer-facing engagements and translate complex technical concepts into business value. • Fluent in Hebrew and English AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law.

Data-AI Lead About Us OurRitual is a fast-growing digital platform reshaping how relationship therapy works. We combine expert-led therapy sessions with AI-powered support to create a blended experience — where clinical depth and intelligent technology weave together into something neither could deliver alone. We call it Continuous Therapy. We've reached product-market fit with strong growth, exceptional engagement, and retention that breaks the category. We're pre-Series A, at the stage where AI moves from feature to foundation — and that shift runs straight through data. Role Overview As Data Lead, you will own how data gets turned into decisions across the company — and lead the shift from traditional BI into AI-driven BI, powered by agents that surface insight in real time. You'll work closely with one data engineer today, with room to grow the team as scope expands. You'll define what the data function looks like when AI is embedded in it, not bolted on — from the underlying infrastructure to the dashboards and agents people actually use. The playbook for AI-native BI is still being written, and you'll write a lot of it. Key Responsibilities Data Strategy & Ownership • Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI • Set priorities in partnership with senior leadership • Work closely with a data engineer today, with the option to grow the team as the function scales AI-Driven BI & Agents • Drive adoption of AI across data workflows — from automating analyses to agents answering business questions in real time • Own the semantic and metrics layer so every dashboard and every agent reads the same definitions • Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents • Expose our data to agents over MCP so business questions get answered without waiting for a dashboard • Define where AI speeds things up — and where human judgment still has to hold the line Infrastructure & Analytics • Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability • Lead complex analytics work, A/B testing, and impact measurement, hands-on • Define evals and quality metrics for AI features and agents — not just A/B tests on dashboards Cross-functional Collaboration • Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions • Represent the data function to the organization — senior-level storytelling with data Skills & Qualifications • 7+ years of experience in data roles, spanning both analytics and infrastructure • Strong analytical foundation — you understand what makes analysis rigorous, not just what makes it automatable, and can use that to build an AI-driven analytics system that's actually trustworthy • Hands-on experience integrating AI into data workflows — building it, not just using it; you've shipped an agent or AI analysis flow that people actually use • Strong SQL skills and experience building scalable data infrastructure • Track record owning data projects independently with stakeholders across the business • Solid grounding in experimentation and statistical methods • Excellent communication and presentation skills at a leadership level • Comfortable being the most senior (and often only) data voice in the room Nice-to-Have Skills • Experience with dbt • Experience with Amplitude • Experience with BigQuery • Experience with git-based BI workflows or tools like Modus • B2C environment experience Why This Role Data teams are about to look very different — not because dashboards disappear, but because people expect answers faster than a weekly report can deliver. This is a rare opportunity to define what AI-native data leadership looks like at a company sitting on a dataset that doesn't exist anywhere else, with real ownership over how the function grows. If you want to build the data function that a category-defining product deserves, this is it.

About the role We’re looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities—from LLMs and agents to product data insights—are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making. Key responsibilities • Lead a team of data scientists, data engineers and product analysts • Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation • Drive excellence, code quality, and best development practices • Provide technical direction and hands-on guidance for complex AI systems • Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences • Ensure AI solutions are safe, scalable, observable, and continuously improving • Lead initiatives around product data analysis and experimentation • Analyze user interactions with product features to improve accuracy, UX, and business impact • Partner with product teams to define metrics, dashboards, and experiments that guide product improvements • Design system architectures for AI-enabled applications at scale • Evaluate and select technologies for AI platforms and data pipelines • Guide the development of prompt engineering frameworks and centralized prompt management • Ensure robust monitoring, evaluation, and feedback loops for AI outputs • Translate product and business goals into technical roadmaps and execution plans • Drive alignment between AI capabilities and measurable product outcomes Requirements • 6+ years of software engineering experience building production-level systems. • 2+ years of engineering management or technical leadership experience. • Strong experience building large-scale backend systems in Python. • Experience developing modern web applications using frameworks such as React / Next / Angular / Vue. • Experience deploying and operating LLM-based systems in production, including evaluation and iteration. • Strong understanding of data pipelines, experimentation, and product analytics. • Experience with modern cloud environments such as Google Cloud Platform or Amazon Web Services. • Passion for clean code, scalable architectures, and data-driven product development. • Experience with prompt engineering, RAG architectures, and vector databases. • Experience building AI agents or autonomous workflows Nice to Have • Experience with frameworks such as ADK, A2A, LangChain, LangGraph, or LlamaIndex or equivalent • Experience with gRPC and protobuf-based architectures • Experience building MCP servers • Background in data engineering, experimentation platforms, or ML infrastructure About april april is the only embedded, year-round tax platform built to power smarter financial decisions. From filing to planning to onboarding, april’s white-labeled tools bring real-time tax intelligence into the platforms people already use, helping users understand the impact of every paycheck, equity transaction, or income shift, and stay on top of tax payments throughout the year. Built to handle even the most complex tax situations, april’s AI-powered tax engine ingests data directly from partner apps to deliver accurate outcomes in record time—making tax planning and filing more connected, contextual, and accessible than ever. With API-first infrastructure and seamless data integrations, april helps partners deliver more value, deepen loyalty, and turn taxes into a strategic edge—for their clients and their business.

Description We’re growing and looking to hire a Director of Data & AI who embodies our core values: People First, Customer Obsession, Strive for Excellence, and Integrity. About the Company: Claroty is a global leader in cyber-physical systems (CPS) protection, dedicated to securing the critical infrastructure that keeps the world running. We’re a fast-growing, award-winning team where innovation meets purpose—and we want you to help us define the future of cybersecurity. At Claroty, our technology strategy is focused on solving real-world cyber-physical security problems at scale through robust, distributed, cloud-native architectures. We design and evolve a unified platform that serves as the technological backbone for all Claroty products, delivering deep visibility across CPS environments—without disrupting critical operations. Our architecture emphasizes scalability, resilience, and extensibility to support both cloud and on-prem deployments. About the Role: We are seeking a visionary Director of Visibility to lead our core technology engine. This is a highly unique role that demands both top-tier professional expertise in cybersecurity research and the ability to seamlessly integrate Data Science and AI in a precise, highly productive manner. Claroty has ambitious visibility goals that require uncompromising accuracy. Your mission is to combine precise, in-depth professional understanding of Cyber-Physical Systems (CPS/XIoT) with the immense scale and capabilities of AI. You will lead a multidisciplinary group comprising Data Science, Network/Protocol Research, and Asset Classification teams to revolutionize how we discover, classify, and secure critical assets across industrial (OT) and healthcare (IoMT) environments. Responsibilities As a Director of Data & AI your impact will be: • Multidisciplinary Leadership: Manage, mentor, and synchronize three distinct teams (Data Science, Network Research, and Asset Classification), ensuring cross-functional synergy and unified product delivery. • Scaling Accuracy with AI: Architect our visibility solutions to achieve unparalleled precision. Blend deep professional domain knowledge with advanced ML to scale asset discovery without sacrificing the exactness required in critical infrastructure. • Feature Engineering & Parsing: Oversee the translation of obscure, undocumented industrial and medical protocols into actionable features for our AI models. • Cross-Department Collaboration: Work closely with various data groups, product management, and R&D teams to translate network visibility into actionable risk management, segmentation, and threat detection policies. • Advanced Data Fusion & Collection Strategy: Manage diverse collection techniques (passive, active, and integrations), and architect how to fuse information for every single device at the scale of AI—bridging applications, algorithms, LLMs, and beyond. Requirements What you need to succeed in this role: • Experience: 7-10+ years of proven experience in network security, cybersecurity research, or data science, with a significant focus on complex networking environments. • Leadership: Demonstrated experience managing R&D, Research, or Data Science groups (e.g., Head of Research, Director of Data Science). • Technical Background: Strong engineering foundation with hands-on experience in reverse engineering, deep packet inspection (DPI), or "black-box" system analysis. • Data & AI Literacy: Deep understanding of the end-to-end Machine Learning lifecycle, data lineage, and the proven ability to leverage AI/ML to scale precise engineering solutions. • Domain Expertise: Familiarity with OT/ICS protocols (e.g., CIP, Modbus) or IoMT protocols (e.g., DICOM), and an understanding of CPS architectural constraints is a major advantage. • Mindset: A highly professional integrator who can speak the languages of data scientists, network engineers, and product managers to foster a collaborative, innovative, and high-performing environment. About Claroty Claroty empowers organizations to protect the mission-critical infrastructure that underpins modern life. The AI-powered Claroty Platform serves as the single source of operational truth, providing the deepest visibility and broadest protection across cyber-physical systems (CPS), leveraging five core solutions: asset inventory, exposure management, network protection, secure access, and threat detection. Claroty helps organizations operationalize CPS protection through a programmatic approach designed to reduce risk, maintain operational integrity, and meet compliance–whether in the cloud with Claroty xDome or on-premise with Claroty Continuous Threat Detection (CTD). Claroty is deployed by hundreds of organizations at thousands of sites globally. The company is headquartered in New York City and has a presence in Europe, Asia-Pacific, and Latin America. To learn more, visit claroty.com. Claroty is widely recognized as the industry leader in CPS protection, backed by the world’s largest investment firms and industrial automation vendors. The company has been named a Leader in 2026 Gartner® Magic Quadrant™ for CPS Protection Platforms two years in a row, a Customers’ Choice in the 2026 Gartner® Peer Insights™ Voice of the Customer for CPS Protection Platforms, and a Leader and a Customer Favorite in The Forrester Wave™: Operational Technology Security Solutions, Q3 2026. Claroty has also been named to the Forbes Cloud 100 and Deloitte Technology Fast 500 multiple consecutive years. Claroty is an equal-opportunity employer committed to fostering a diverse and inclusive work environment for all. We encourage applications from candidates of ALL diverse backgrounds, and special accommodations are available upon request in all selection phases. Follow us on social media: • LinkedIn • LinkedIn Life Page • Facebook • Instagram