AI Engineer jobs in Tel Aviv-Yafo

Who are we? Skai (formerly Kenshoo) is a leading omnichannel marketing platform that leverages advanced AI and data-driven performance media to enable smarter decision-making, increased efficiency, and maximized ROI for businesses worldwide. Our platform helps manage approximately $10B in annual ad spend through partnerships with Google, Meta, Amazon, Microsoft, and others. Founded in 2006, Skai is a global company with around 650 employees. We operate in a hybrid work model that combines remote flexibility with in-office collaboration. What will you do? As an AI Engineer, your primary focus will be delivering working features while adopting a Builder Mindset to shape the future of software development at Skai. You will leverage cutting-edge GenAI tools (such as Claude Code and others) to accelerate development, streamline workflows, and bring high-quality, production-ready features to life. In this role, you will work closely with PMs, designers, and fellow engineers across frontend, backend, and data domains. You will use AI to tackle complex debugging, conduct research, and eliminate repetitive tasks—continuously improving your productivity while delivering functional, impactful features within your pod. Responsibilities: Feature Delivery: Own and deliver working features from end to end, contributing production-ready code with guidance and driving tangible product value. AI-Accelerated Development: Utilize GenAI tools (e.g., Claude Code) to accelerate feature development, improve personal productivity, and optimize daily workflows. Problem Solving & Debugging: Leverage AI for rapid debugging, technical research, and reducing repetitive manual work during feature delivery. Cross-Domain Collaboration: Build a solid understanding across product, frontend, backend, and data domains, collaborating effectively with PMs, designers, and engineers. Context & Documentation: Document technical decisions clearly and contribute to building shared team context and knowledge bases. Continuous Learning & Adaptability: Learn the tech stack quickly, adapt smoothly to new tools/workflows, and actively apply feedback to grow as a builder. Pod Reliability: Act as a dependable, collaborative contributor within your pod, helping drive team momentum and execution. Requirements 2–5 years of experience in software development. Relevant Academic Degree (B.Sc. in Computer Science, Software Engineering, or related fields) OR Relevant Military Experience (e.g., tech/intelligence units such as 8200, Mamram, Ofek, etc.). Builder Mindset: Strong passion for GenAI tools (such as Claude Code, etc.) and a proven desire to integrate them into daily coding workflows. Ability to quickly learn new tech stacks, adapt to changing tools, and translate feedback into rapid growth. Strong cross-domain curiosity - eager to understand product context, backend logic, frontend UX, and data flow. Excellent communication skills and a strong collaborative mindset in a hybrid working environment.

Conifers is transforming security operations centers (SOCs) with CognitiveSOC™, its AI SOC platform, enabling enterprises and MSSPs to achieve SOC excellence. By leveraging agentic AI, Conifers helps security teams investigate complex, multi-tier incidents with speed, accuracy, and trust. Led by seasoned cybersecurity leaders and backed by SYN Ventures, PICUS Capital, and others, the company brings deep industry knowledge and innovation to an increasingly AI-driven threat landscape. We’re building an AI-native security platform that enables autonomous agents to investigate real-world threats at a massive scale. About The Role : You’ll build real AI systems running in production, where intelligent agents and robust backend architecture work together to investigate security incidents for real customers. If you enjoy turning cutting-edge AI into reliable, scalable production systems, you’ll feel at home here. What You’ll Do : • Design, build, and ship major end-to-end features • Lead development of AI agents operating in production environments • Architect and scale Python-based distributed backend systems • Make key technical decisions that shape the evolution of an AI-first platform • Build systems that combine LLMs, reasoning flows, orchestration, and classic backend engineering • Work closely with Product, Design, Security Researchers, and GTM teams • Bring clarity, ownership, and strong engineering standards to the team What You’ll Bring : • 5+ years of software engineering experience • Strong software engineering background, with the ability to build production-grade systems beyond research, experimentation, or prompt engineering • Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems • Strong backend expertise, including Python, distributed systems, and cloud-native architecture • Experience designing systems that balance AI components with reliable backend infrastructure • Ability to take ambiguous problems and turn them into structured, scalable solutions • Strong ownership mindset and bias for action • Full professional fluency in English Nice to Have : • Experience in the cybersecurity domain • Experience building security or AI-driven products • Experience working in a fast-paced startup environment Our Commitment : We are an equal opportunity employer and value diversity at our company. All qualified applicants will receive consideration without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #LI-AM1 #LI-Hybrid

About Us OurRitual is a fast-growing digital platform revolutionizing relationship guidance. We provide expert-led sessions, personalized pathways, and engaging content to help individuals and couples work through relationship challenges. We are now scaling and looking for the right people to join our (great!) team to continue delivering exceptional experiences to our users. Role Overview We are looking for a Generative AI Engineer to lead our AI efforts end-to-end — from infrastructure and production systems to internal adoption and cross-team enablement. You will play a significant role in building the world's first Consumer Therapy AI Product (someone said RAG? But we mean a real one that works in production...). This is a critical role in a high-growth, fast-paced B2C startup, requiring a leader who can advocate for Engineering requirements, tech-debt and best practices while promoting a product-mindset and putting our customers front and center. About You • You are a great human being and you’re all into teamwork. you care about how people will feel inside the organization and set high standard for culture, professionalism and maturity. • A Doer, hands-on, biased for action and not taking an advisory role. Know how to translate challenges into actions. Able to work both individually and manage multiple priorities while driving others around you for action. • You're a fast learner, jack of all trades, feel comfortable in a fast paced, ever-changing environment. You can break down complex problems into steps and plot clearly how to get from A to Z while having the ability to zoom out and see the bigger picture. • You are an experienced hands on engineer, with proven experience with Developing LLM based products, with a real passion to AI and LLM, eager to learn about very new model and technology in this domain, and have a real understanding of the AI ecosystem. Key Responsibilities AI Infrastructure & Production • Own and design GenAI architecture (LLMs, pipelines, agents) • Build and ship AI features into production • Integrate enterprise models (OpenAI, Anthropic, Google) • Optimize cost, latency, and reliability (tokens, caching, evals) • Handle real-world constraints (context window, hallucinations) Prompt Engineering & Product Collaboration • Lead prompt design and experimentation across teams • Work with product, copy, and operations on AI-driven features • Build and evaluate prompt pipelines (quality, consistency) Research & Innovation • Stay up to date with GenAI ecosystem (models, tools, frameworks) • Evaluate and implement frameworks (LangGraph, LangChain, etc.) • Prototype quickly and iterate in a startup environment Required Skills & Qualifications • ~1+ year experience with Generative AI / LLMs • 5+ years experience with Backend engineering • Experience shipping GenAI features to production • Strong hands on, production grade backend/software engineering skills (Python preferred) • Experience with major AI providers (OpenAI, Anthropic, Google) • Prompt engineering and LLM behavior knowledge • Understanding Agents / multi-step workflows • Experience with AI frameworks (LangChain, LangGraph, etc.) • Familiarity with embeddings / vector databases • Excellent problem-solving skills with demonstrated success in fast-paced environments. Bonus • MLOps / model deployment experience • Evaluation, monitoring, and guardrails • Fine-tuning or model customization • RAG systems (Retrieval-Augmented Generation) • Building retrieval pipelines and grounding LLM outputs

Description You'll design the architecture that lets AI run compliance at scale. Sedric is the AI compliance platform for financial services. Our agentic AI automates oversight across customer communications and marketing — real-time guardrails on calls, pre-approval review on every marketing asset, and post-publication monitoring across partners and channels. Because every customer gets a dedicated compliance model, accuracy goes up, false positives go down, and compliance teams move faster without taking on more risk. AI isn’t a feature at Sedric — it’s the product. Every agent, LLM flow, and retrieval pipeline that runs a customer’s compliance program runs on backend systems someone has to design, build, and keep fast, accurate, and cost-efficient at scale. We’re looking for a hands-on AI engineer who designs those systems and writes the code. You’ll own the architecture of our AI backend end to end, ship it to production, monitor how it performs with real customers, and raise the bar for the engineers around you through code reviews, design reviews, and mentoring. The mission? We're at an inflection point. Enterprise financial services clients are signing on, and they need more than a product — they need a platform. That means a unified LLM strategy, an architecture that scales, and an R&D org that moves with the same urgency as the business. This role reports to the AI team Dev Team Lead and is based in Tel Aviv (hybrid model). This is a hands-on engineering role. It’s not a research position and not a people-management role. You’ll spend most of your time designing and building production systems. What You’ll Own You'll own Sedric's AI reference architecture end to end — the patterns, standards, and platform capabilities that every AI initiative across engineering builds on. You'll lead architecture reviews, set the technology roadmap, and make the call on what we adopt, pilot, or retire. • Design and build the backend architecture for Sedric’s AI agents, LLM pipelines, and retrieval systems, and write a large share of the production code yourself • Take AI capabilities from prototype to production in a multi-tenant SaaS environment • Optimize for scale and cost: model selection, prompt and token efficiency, caching, batching, latency, and infrastructure spend • Build monitoring and evaluation for AI quality in production (accuracy, false positives, drift, cost per customer) and act on what it shows • Set engineering standards for AI development and mentor engineers through pairing, code reviews, and design reviews • Bring new AI techniques into the product when they solve a real customer problem, and prove it in production Requirements You're a fit if… • You have 5+ years of ML/AI architecture experience in a SaaS company • 3+ Backend development experience • You bring both the technical depth and the leadership range this role demands. • You've built agentic systems with tool use, planning, and multi-step reasoning in production, not just in a notebook • You've set up AI governance and evaluation harnesses from scratch • You have proven, hands-on experience with AI in production systems • You can take a project from concept to shipped and interface with stakeholders the whole way • You hold a relevant degree; an advanced degree in CS, ML, Statistics, or a related field is a plus • You're comfortable in front of customers and executives, translating technical tradeoffs into business terms You're probably not a fit if… • You want to execute against someone else's architecture, not design your own • You'd rather avoid customer or stakeholder conversations than lead them • You think about the technology and skip the business context it lives in • You need long runway before shipping — this role moves fast and mixes design with execution • You want a playbook handed to you rather than writing the first one What Success Looks Like Your first 90 days goals: • Day 30 — You understand the AI architecture of the platform end to end — the systems, the constraints, the decisions already made. • Day 60 — You've shipped LLM-driven improvements and optimized existing flows for latency and reliability. • Day 90 — You own AI design across the platform — teams come to you before they build, not after. Compensation & Benefits • Competitive salary aligned with industry standards • Meaningful equity in a high-growth compliance AI company • Direct access to leadership — no bureaucracy between you and impact • Flexible, output-first culture — we care what you ship, not when you log on • Work on problems that matter in an industry that’s ready to change How to Apply & Important Notice Do you think that this is for you? apply directly or send your resume to [email protected]. Equal Opportunity Employment Sedric.Ai is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or protected veteran status. AI & Recording Disclosure: To streamline our hiring process and ensure a thorough review, Sedric.Ai utilizes AI-powered tools to evaluate resumes, and our interviews may be recorded or assisted by an AI note-taker. By submitting your application, you acknowledge and consent to the use of these technologies during the recruitment process. If you prefer to opt out of AI resume screening or interview recordings, please notify our recruiting team at [Insert Contact Email/Link] to request a manual review or unrecorded interview.

We are making the future of Mobility come to life starting today. At Autofleet we support the world's largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization. We are looking for a talented AI Engineer to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes. What You’ll Do • Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions • Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails. • Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback. • Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead. • Collaborate with engineering teams to design, build, and maintain production pipelines. Requirements • Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline. • 5+ years of software engineering experience, with proven ability to build production-grade systems beyond research, experimentation, or prompt engineering. • Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems. • Strong backend expertise, including Python, distributed systems, and cloud-native architecture. • Familiarity with the AI Agents ecosystem, including different LLM providers, vector store solutions, MCPs, A2A and more. • Familiarity with REST APIs and integrating external data sources.

LEDGE'S MISSION is to reinvent how finance teams work by building AI agents that actually do the work, not just automate it. We began with an industry-leading reconciliation platform used by top finance teams. We are now broadening our scope to develop a completely AI-native close management solution, built upon our strong existing platform that is already competitive with leading industry offerings. Our agents autonomously prepare, reconcile, validate, and manage the close end-to-end with finance-grade accuracy and transparency. We’re designing new tools for the Office of the CFO: a scalable, trustworthy data pipeline combined with autonomous AI workflows and a clean, consumer-grade experience. As an AI-first engineering organization, we use modern microservices, full IaC, and advanced AI coding and development tooling to move fast and build real autonomy into the finance workflow. ‍ The role AI Engineers at Ledge take true end-to-end ownership from scoping agent behaviors and designing model-driven architectures to deploying and monitoring production AI systems. You’ll help evolve our reconciliation engine and build the next generation of AI agents powering the automated financial close, solving deep technical, data, and product challenges in partnership with accounting and finance experts. ‍ What we are looking for • Experience building or orchestrating AI agents • Background in model evaluation, prompt engineering, or autonomous workflow design • You thrive in a fast-paced startup environment and are willing to work hard to achieve ambitious goals • You have a get-things-done attitude and deliver high-quality work quickly • You have 5+ years of software engineering experience, including building or integrating AI systems • You are a proactive team player motivated to impact the team, the product, and the customers • You have strong fundamentals in distributed systems, data flows, and cloud/web architectures • You are an independent, fast learner excited about mastering new AI technologies and tooling ‍ Nice to have • Experience with payments, accounting, or finance • Experience working on AI-first teams or with LLM-based systems • Experience developing high-performance, real-time, customer-facing applications • Experience with typescript and nodeJs

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team. The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows. You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations. Your Impact AI Agent Development • Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows. Workflow Automation • Build machine learning pipelines to automate content-heavy processes for enterprise businesses. Model Optimization • Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy. Collaboration • Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations. Evaluation & Testing • Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios. What It Takes Experience • 5+ years of experience as a software engineer or data scientist building production systems. • 2+ years of experience with large language models and NLP techniques. • Background in developing AI agents for content heavy tasks. • Experience with multiple LLM Vendors, RAG or Fine Tuning OSS or Commercial models. Technical Skills • Proficiency in Python and machine learning libraries such as TensorFlow or PyTorch. • Deep understanding of LLM architectures and NLP applications like entity recognition, document classification, and summarization. • Experience with model grounding techniques, retrieval-augmented generation (RAG), and deploying robust AI models in production environments. • Skills in designing and deploying AI models through APIs, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure). • Understanding of best practices for continuous monitoring, evaluation, and iterative improvement of deployed models.

Description We're transforming how software gets built, with GenAI at the center of the development lifecycle. As an AI Transformation Engineer, AI transformation is your day-to-day focus. You'll design and build the agentic workflows, tools, and AI infrastructure our engineering teams rely on. You'll also take on business projects that need hands-on AI development, so the work stays varied. We're looking for a highly technical engineer who takes ownership of open-ended challenges, leads independently, and delivers results that move the needle. What You'll Do • Drive AI transformation across the SDLC: design, build, and ship agentic workflows for planning, coding, testing, code review, and security remediation, from prototype through production • Lead business-driven AI projects when needed, from understanding the product need to delivering the solution • Find what's worth automating: work with engineering teams, architects, and product managers to find high-impact use cases • Engineer the harness: design and manage agent context, knowledge, tools, and scaffolding, and build evals that keep agents reliable at scale • Own outcomes, not just tasks: turn broad goals into clear metrics such as adoption, throughput, cycle time, and quality, and show what your work moved Requirements • 5+ years of hands-on software engineering experience (TypeScript/Node.js, Java or Python) • Hands-on experience building and shipping LLM-powered systems or agentic workflows in production • Strong harness engineering skills: hands-on with Claude Code, GitHub Copilot, or similar tools, with a deep understanding of how to build, scaffold, and manage agent context at scale • Working knowledge of LLMs, RAG, tool use, MCP, evaluations, and human-in-the-loop patterns • Solid experience with CI/CD, GitHub Actions, and cloud platforms, preferably Azure • Proven ability to lead independently, bring structure to open-ended problems, and deliver measurable results • Highly technical, yet not afraid to dig into the product and understand the business side • Lives and breathes AI: stays current on the latest models, tools, and practices, and brings new ideas to the team • Strong communication skills and a team-player mindset Advantages: • Experience developing AI-SDLC / AI-PDLC solutions • Experience building a company brain or organizational knowledge layer at scale • Experience building agent verification solutions at scale, such as automated E2E testing with Maestro or similar frameworks • Proven track record of leading cross-team projects and aligning stakeholders with different priorities • Experience with agent orchestration frameworks, agent factories, or multi-agent systems • Familiarity with observability tooling for monitoring agent and platform health Why You'll Love Working With Us • Real impact at scale: what you build changes how an entire organization develops software • GenAI at the core: we don't just use AI, we build it into our engineering DNA • Learning & growth culture: every engineer has a personal professional growth plan We are hiring for various positions within the company, with some roles offered through outsourcing. Join us and enjoy a dynamic and flexible work environment.

AI Platform & Innovation Engineer We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv. This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across Nexxen’s products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company. What You’ll Do • Design and build reusable AI platform capabilities used across multiple products. • Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities. • Design and build internal AI platforms such as organizational knowledge (“Brain”), AI developer tools, autonomous engineering workflows, and shared AI services. • Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform. • Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities. • Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment. • Build and operate production AI services using modern cloud-native technologies. • Improve the reliability, scalability and observability of AI systems. • Define engineering standards, reusable patterns and best practices for AI development across engineering teams. • Lead technical proof-of-concepts and drive adoption of innovative AI technologies. • Mentor engineers and provide technical leadership on complex AI initiatives. What You’ll Bring • B.Sc. in Computer Science or a related field. • 5+ years of backend software engineering experience. • 3+ years of hands-on experience building production AI systems. • Strong Python development experience – Must. • Hands-on experience with Kubernetes, Docker and deploying production workloads in cloud-native environments – Must. • Hands-on experience with CI/CD pipelines, GitOps workflows and modern software delivery practices – Must. • Deep understanding of Large Language Models (LLMs), prompting, reasoning techniques, structured outputs, tool calling and retrieval architectures – Must. • Strong experience designing and building end-to-end AI systems, from data ingestion and orchestration to production deployment. • Experience designing AI agents, agentic workflows or AI automation systems. • Experience working with Data Science or Machine Learning teams. • Strong software architecture and distributed systems design skills. • Experience with vector databases, graph databases or modern AI data platforms – an advantage. • Experience with AI frameworks such as LangGraph, OpenAI Agents SDK, CrewAI, Semantic Kernel, AutoGen or similar – an advantage. • Experience evaluating and integrating emerging AI technologies into production systems – an advantage. • Excellent spoken and written English skills. • A proactive, curious and collaborative mindset, with a passion for building AI platforms and driving technical innovation across engineering teams. What if I have any questions before I apply? All applications need to be submitted online, however, to discuss any adjustments you may require ahead of submitting your application, please email [email protected] #LI-DK1 #LI-HYBRID At Nexxen, we value our differences, varied experiences, and collective contribution. We know that not everyone takes the same career path, so if you don’t match this job description perfectly, don’t worry! We would rather see your application than risk missing out on your potential to make an impact. For information about how we handle your personal information please view our Applicant and Candidate Privacy Notice Important Notice from Nexxen: Your Safety Matters At Nexxen, we care about the well-being of our current and future employees. We are aware of the growing number of online scams and fraudulent job postings, and we urge all job seekers to remain vigilant. Please be advised that Nexxen will never request payment (whether in cash, cryptocurrency, or any other form) as a condition of employment, offer positions that require you to invest in vague or dubious financial schemes, or promote roles that resemble get-rich-quick opportunities. If you receive a suspicious message claiming to be from Nexxen or encounter a questionable job posting associated with our name, please contact us at [email protected] to verify its legitimacy. Your trust is important to us. Stay safe and informed. Nexxen Fraud Alert and Notice: Protect Yourself from Impersonation and Fraudulent Activity

Description We are looking for a highly technical, hands-on Quality Engineering Lead to drive product quality through AI-powered automation, intelligent testing, and proactive issue detection. Your mission is to build and continuously improve automated quality mechanisms that identify bugs, regressions, performance issues, and unexpected system behavior before they impact our customers. You will leverage AI agents, modern development tools, and engineering automation to make quality an integral and continuous part of our development lifecycle. This is a senior, hands-on technical leadership role with ownership of the Quality Engineering domain across R&D. You will define the technical direction, lead cross-team initiatives, and establish the foundations for a scalable, AI-driven quality engineering function, with the opportunity to build and lead a dedicated team as the domain evolves. We are looking for someone who combines strong software engineering expertise, a passion for product quality, and the leadership skills to drive meaningful change across the engineering organization. Responsibilities • Build AI-Powered Quality Agents: Design and implement agents that proactively identify bugs, regressions, and unexpected behavior across our systems. • Develop Intelligent Testing Mechanisms: Build automated testing solutions that leverage AI to generate, execute, and maintain meaningful test scenarios. • Proactive Issue Detection: Analyze logs, metrics, traces, production behavior, and code changes to identify potential quality issues. • Automate Regression Detection: Develop mechanisms that continuously validate system behavior and detect regressions introduced by new releases. • Improve Release Confidence: Build automated quality gates and validation mechanisms integrated into CI/CD pipelines. • Production Quality Monitoring: Develop intelligent mechanisms that detect functional inconsistencies, data integrity issues, and unexpected production behavior. • AI-Assisted Root Cause Analysis: Build tools and agents that investigate detected issues, identify likely causes, and provide actionable findings to engineering teams. • Drive Quality Engineering Across R&D: Collaborate with all engineering teams to identify quality gaps, establish best practices, and drive the adoption of AI-powered quality mechanisms throughout the development lifecycle. • Technical Leadership & Ownership: Own and lead the Quality Engineering domain across R&D. Define the technical direction, drive cross-team initiatives, establish engineering standards, and mentor engineers working on quality-related solutions. • Build and Scale the Quality Engineering Function: Establish the technical foundations, processes, and tools needed to scale quality engineering across the organization, with the potential to build and lead a dedicated team. • Own Quality Improvements End-to-End: Independently design, develop, deploy, and maintain quality engineering tools and automation, ensuring measurable improvements in product quality. Requirements • 7+ years of hands-on software engineering, quality engineering, or test infrastructure development experience. • Proven technical leadership experience as a Tech Lead, Staff Engineer, or equivalent, with the ability to drive cross-team initiatives and influence engineering practices. • Strong programming skills in Python, TypeScript, or similar languages. • Extensive experience building automated testing frameworks, quality validation systems, or engineering automation infrastructure. • Hands-on experience using LLMs, AI coding tools, or AI agents to solve engineering problems. • Strong understanding of backend systems, APIs, distributed architectures, and cloud environments. • Experience with CI/CD pipelines, integration testing, and automated regression testing. • Strong debugging, troubleshooting, and root cause analysis skills. • Ability to define technical direction, mentor engineers, and take ownership of an engineering domain across the organization. • Strong communication and collaboration skills, with the ability to work effectively across multiple engineering teams. • Ability to independently identify quality gaps and deliver production-ready engineering solutions. Nice to Have • Experience building autonomous AI agents or agent-based testing frameworks. • Experience with Claude Code, Cursor, Codex, or similar tools. • Experience with Kubernetes, AWS, and microservices architectures. • Experience with observability platforms such as Datadog, Groundcover, or Grafana. • Experience with performance testing, chaos engineering, or production validation. • Familiarity with MCP, LLM tool calling, and agent orchestration. • Experience establishing or leading quality engineering initiatives across multiple development teams. • Experience building or scaling engineering teams or technical functions. What Success Looks Like • Critical bugs and regressions are detected before reaching customers. • Automated quality mechanisms continuously validate product behavior across development and production environments. • AI agents reduce manual testing, debugging, and investigation efforts. • Engineering teams receive actionable quality findings early in the development cycle. • Release confidence increases while maintaining or improving development velocity. • Product quality improves through measurable reductions in escaped defects and recurring incidents. • Quality engineering becomes a shared, AI-powered capability adopted across all R&D teams. • A scalable quality engineering function is established, with clear technical ownership, standards, and long-term direction. Our Vision Build an engineering organization where quality is continuously and proactively validated through intelligent automation and AI agents. • We believe quality should not depend solely on manual testing or reactive bug fixing. Our goal is to create an AI-driven quality engineering function that continuously identifies problems, prevents regressions, and empowers every engineering team to deliver reliable software faster.

Description #Hybrid DriveNets builds high-performance networking solutions for large-scale AI infrastructure and service-provider networks. DriveNets’ Network Cloud powers production networks at global operators such as AT&T and Comcast, while its AI Fabric solutions optimize the performance and time to first token (TTFT) in multi-vendor AI environments at foundation model labs, NeoClouds, and enterprises. DriveNets combines high-performance networking, end-to-end automation, and full-stack AI cluster optimization to remove network bottlenecks, maximize GPU utilization, accelerate AI cluster deployments, and improve token economics Job Summary We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our DriveNets Automation Platform (DAP) team. The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments. You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure — running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns. This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems — not model training or research prototypes. Requirements • 8+ years of hands-on software engineering experience building production-grade backend services, APIs, or AI-powered systems. • Proven production experience with multi-agent AI systems: deployment, tracing, guardrails, hardening, and incident management. • Hands-on experience with agentic frameworks such as LangGraph, CrewAI, Google ADK, AutoGen, or equivalent. • Experience building and running evaluation pipelines for agentic solutions - including trajectory tracing, ground truth validation, and harshness/quality scoring. • Strong Python proficiency: comfortable building scalable backend services using gRPC and REST APIs. • Solid understanding of distributed systems: fault tolerance, consistency models, service communication, and operational challenges at scale. • Hands-on Kubernetes experience: deploying and operating containerized services, managing workloads, config, and scaling in production clusters. • Practical experience with embeddings, vector databases, and semantic retrieval systems in production. • Practical experience with RAG pipelines, LLM API integration, structured outputs, and tool calling in production environments including building and serving MCP servers at scale. • Working knowledge of SQL and/or NoSQL databases, schema design, and query optimization. • Strong debugging skills across application logic, APIs, data, and AI agent behavior. • Strong communication skills and a bias toward ownership and delivery. Nice to Have • Familiarity with Langfuse/Arize Pheonix. • Familarity with A2A & A2UI protocols. • Experience with network automation, orchestration, or configuration management (Ansible, Terraform, NETCONF, gNMI, or similar). DriveNets is on a mission to build a special company comprised of individuals with diverse backgrounds, perspectives, and experiences. DriveNets is an equal opportunity employer. We do not discriminate based on upon race, religion, national origin, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with disability, or other applicable legally protected characteristics.

Description A winning ad could change the trajectory of a mobile game. The only way to consistently find winners is to explore more, faster, and smarter than anyone else. Sett is a UA creative performance platform for mobile gaming. We build agentic AI systems that analyze performance data, generate diverse playable and video ad concepts, deploy them to ad networks, and continuously learn from the results. The full creative loop. Automated, and done better than humans only. Our system doesn't remix templates. It creates fundamentally different creative hypotheses, each one built from real performance signals. Sett is looking for a Senior AI Software Engineer to join our out-of-this-world, cross-functional team. If you’re someone who loves taking ownership, enjoys working across the stack, and isn’t afraid to dive into new technologies - this might be your perfect role. Responsibilities • Own end-to-end feature development - from design and coding to testing and production • Work on LLM based applications including the development of proprietary AI agents • Collaborate with team members through design/code reviews and open discussions • Partner closely with research and engineering to deliver impactful solutions Requirements • At least 8 years of experience in software development - a MUST • Strong hands-on experience with Python (at least 4 years) • Minimum 2 years of experience as an ML Engineer, Data Scientist, or in a similar AI-focused role - a MUST • Proven ability to develop and maintain complex backend systems • Curiosity, drive, and a passion for building great tech

Description A winning ad could change the trajectory of a mobile game. The only way to consistently find winners is to explore more, faster, and smarter than anyone else. Sett is a UA creative performance platform for mobile gaming. We build agentic AI systems that analyze performance data, generate diverse playable and video ad concepts, deploy them to ad networks, and continuously learn from the results. The full creative loop. Automated, and done better than humans only. Our system doesn't remix templates. It creates fundamentally different creative hypotheses, each one built from real performance signals. You'll build products where AI isn't a feature - it's the product. From customer-facing experiences to the multi-agent systems behind them, you'll own problems end-to-end, ship continuously, and help define how people work with AI. Responsibilities • Build customer-facing AI products from idea to production. • Design and build AI agents that solve real customer problems. • Create and improve agentic workflows using LangGraph, LangChain, and the Claude Agent SDK. • Build the orchestration layer that lets multiple AI agents collaborate, reason and complete complex tasks. • Own features end-to-end, from React UI to Python backend. • Design APIs and distributed services powering our agentic platform. • Improve reliability, observability and performance across production AI systems. • Work closely with Product, Design and AI Engineers to ship continuously. Requirements • You have 6+ years of experience building web products with Python, React, and TypeScript. • You know how to design clean APIs and scalable architectures. • You have experience with AWS, Docker, Kubernetes, and microservices. • You care about reliability, observability, and production quality (logs, metrics, tracing, and monitoring). • You have built or worked on production AI applications using tools like LangGraph, LangChain, the Claude Agent SDK, or similar frameworks. • You like shipping fast, owning problems end-to-end, and working across the entire stack. • You enjoy solving ambiguous problems and turning ideas into production software

About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role This is a AI Software Tech Lead, ML role within Aidoc’s AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products. Responsibilities • Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging. • Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features. • Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems • Develop and maintain high-quality, scalable, and efficient code. • Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems) Requirements • BA/BSc/MSc in Computer Science, Engineering or a related field. • 7+ years of experience in developing large scale production systems – including architecture design, research, development and testing. • Deep understanding of Computer Science fundamentals – object-oriented design, code optimization, and complexity • Passion for building generic and robust software architecture • Passion for elegant and effective technological solutions, and a love for clean code • Strong experience with Python and advantage to deep learning frameworks such as TensorFlow, PyTorch, etc. • Strong ability to lead end-to-end development processes • Advantage: Experience in developing AI and machine learning solutions, with a focus on computer vision and NLP. • Strong communication and collaboration skills, with the ability to work effectively with a cross-functional team Working at Aidoc Our Perks: • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. • Amazing and healthy breakfasts and lunches prepared daily by our personal chef! • Stocked up kitchen & meal card • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. • Amazing culture - collaborative, transparent & fun! • Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Description We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team. The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows. You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations. Your Impact AI Agent Development • Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows. Workflow Automation • Build machine learning pipelines to automate content-heavy processes for enterprise businesses. Model Optimization • Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy. Collaboration • Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations. Evaluation & Testing • Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios. Requirements What It Takes Experience • 5+ years of experience as a software engineer or data scientist building production systems. • 2+ years of experience with large language models and NLP techniques. • Background in developing AI agents for content heavy tasks. • Experience with multiple LLM Vendors, RAG or Fine Tuning OSS or Commercial models. Technical Skills • Proficiency in Python and machine learning libraries such as TensorFlow or PyTorch. • Deep understanding of LLM architectures and NLP applications like entity recognition, document classification, and summarization. • Experience with model grounding techniques, retrieval-augmented generation (RAG), and deploying robust AI models in production environments. • Skills in designing and deploying AI models through APIs, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure). • Understanding of best practices for continuous monitoring, evaluation, and iterative improvement of deployed models.

Description Upwind is a next-generation Cloud Security Platform that uses runtime context to identify and prioritize critical risks. Unlike traditional tools, Upwind uses runtime data to prioritize risk and inform posture, so teams can focus on what truly matters. Our eBPF-powered sensors and agentless cloud discovery deliver real-time threat protection, posture management, and API security. Together they protect cloud infrastructure end to end, from misconfigurations to malware. At Upwind, you'll have room to think creatively, explore new ideas, and make a real impact on our growth. We're looking for a hands-on AI Engineer to join Upwind's Research team. You'll help build our core intelligence engine: LLM agents that run cloud security workflows end to end. These agents investigate runtime detections, reason over workload, identity, and cloud context, and drive remediation in production. You'll research new models and agent designs, run rigorous experiments, and ship what works as high-impact features in our platform. What you will do • Build LLM-based agents that investigate, triage, and remediate cloud security threats. • Own the path from research to production: prototype new models, techniques, and agent designs, and ship the ones that work. • Train, fine-tune, and evaluate models for security tasks using Upwind's vast data sources: runtime events, cloud logs, identity, and network activity. • Build and extend our internal AI platform: services, pipelines, evals, and observability. • Collaborate with Security Researchers, Product, and Engineering to turn research findings into production-grade autonomous workflows. Requirements • 3+ years building AI/ML systems in production, including LLM-based agents built with modern AI and agent frameworks. • Strong backend engineering skills and proficiency in Python. • Experience training or fine-tuning ML models and LLMs. • Strong understanding of AI system reliability: prompting and context engineering, evaluation pipelines, LLM-as-judge, regression testing, and production monitoring. • Proven AI research ability: track the literature, frame open problems, design rigorous experiments, and benchmark new techniques against the state of the art. • Strong ownership and the ability to work both independently and as part of a team in a fast-paced environment, bridging research and product engineering. • Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Nice to have • Background in cybersecurity (e.g., cloud security, threat detection, incident response). • Hands-on experience with cloud platforms (AWS, GCP, Azure) and Kubernetes. • • Research publications, open-source contributions, or other work that shows depth in AI.

Description Upwind is a next-generation Cloud Security Platform that leverages runtime context to identify and prioritize critical risks, providing precise insights and efficient cloud security management. Unlike traditional tools, Upwind uses runtime data proactively for risk prioritization and posture insights, ensuring teams focus on what truly matters. With industry-leading efficiency and eBPF-powered sensors, Upwind delivers comprehensive capabilities, including agentless cloud posture discovery, real-time threat protection, and integrated API security. From misconfigurations to malware defense, Upwind ensures end-to-end, cost-effective cloud infrastructure protection. At Upwind, you'll have the opportunity to work on some of the most challenging problems in applied AI and security, turning cutting-edge research and LLM capabilities into products that operate in real customer environments. We're looking for an AI Engineering Lead to help drive the quality, intelligence, and continuous improvement of Upwind's AI and agentic systems. This is a hands-on AI engineering lead role focused on data, evaluation, and agentic workflows. You'll build the systems and methodologies that allow us to understand how our agents perform, identify where they fail, and continuously improve their reasoning, tool usage, and outcomes. You'll work closely with AI Researchers, Engineers, and Product teams to turn experiments into reliable, high-performing AI systems — from defining evaluation datasets and metrics to improving agentic workflows and deploying them at scale. What You’ll Build: • Agentic Workflows: Design and continuously improve multi-step agent workflows, including reasoning, tool usage, planning, state management, and recovery strategies. • AI Evaluation: Build evaluation frameworks, datasets, metrics, and automated pipelines to measure the quality and reliability of LLMs and agents. • AI Data Infrastructure: Build the data pipelines and feedback loops required to collect, curate, analyze, and learn from real-world agent interactions • AI Observability: Build visibility into agent behavior and performance, including trajectories, tool calls, latency, failures, and outcome quality. Responsibilities: • Own and evolve the evaluation strategy for Upwind's AI agents and LLM-powered features. • Define meaningful metrics and automated evaluation pipelines for measuring agent quality, accuracy, reliability, and task completion. • Design and improve agentic workflows to make agents more capable, reliable, efficient, and predictable. • Build feedback loops from production usage back into evaluation datasets and development workflows. • Develop tooling for running experiments and comparing models, prompts, workflows, and agent configurations. • Work closely with AI Researchers to turn research ideas and experiments into production-quality AI capabilities. • Collaborate with backend engineers to integrate AI workflows and evaluation systems into our production platform. • Establish best practices for testing and validating non-deterministic AI systems. • Monitor AI systems in production and continuously identify opportunities for improvement. • Take end-to-end ownership of projects- from defining the problem and building the first experiment to productionizing and measuring its impact. Requirements • Strong engineering experience, with a track record of owning and delivering complex technical systems. • Hands-on experience building LLM-powered applications, agents, or AI systems. • Strong understanding of LLM evaluation, experimentation, and data-driven development. • Experience designing and implementing LLM-as-a-Judge evaluations, including evaluation criteria, scoring rubrics, structured outputs, and validation of judge reliability. • Strong problem-solving skills and the ability to analyze complex AI behavior and turn observations into concrete improvements. • Experience working with agentic workflows, tool calling, multi-step reasoning, or AI orchestration. • Ability to work closely with researchers and engineers and bridge the gap between experimentation and production. • Comfortable working in a fast-paced environment where requirements and technologies evolve quickly. Strong Advantages: • Experience with LLM evaluation frameworks and automated evaluation pipelines. • Proven experience with LLM-as-a-Judge methodologies, including calibrating judges against human evaluations, measuring evaluator consistency, and reducing evaluation bias • Experience with LangGraph, LangChain, or comparable agent orchestration frameworks. • Experience working with security, infrastructure, or other complex technical domains. • Experience building production AI systems where correctness and reliability are critical. • Strong Python skills and experience working with data processing and AI/ML tooling. Why Upwind? • You'll have the opportunity to work on AI systems that are solving real, complex security problems- not demos or prototypes. • You'll be part of a team building the next generation of AI-powered security agents, with the opportunity to influence how we evaluate, improve, and scale these systems from the ground up.

Job Description • Agentic Framework Design: Design and implement intelligent, multi-agent AI systems capable of executing complex security analysis workflows and automated decision-making. • Context Optimization: Analyze diverse security datasets to determine the most effective context, telemetry data, and threat intelligence to feed into AI agents to maximize decision accuracy and minimize false positives. • Model Configuration & Integration: Evaluate, configure, and deploy a variety of state-of-the-art language models and AI architectures tailored for high-performance security use cases. • Data Analysis & Performance Evaluation: Perform deep data analysis on security events and model outputs to continuously refine agent logic, benchmark performance, and optimize AI-driven detection mechanisms. • Collaboration & Deployment: Partner with security research and engineering teams to integrate intelligent AI components into production systems seamlessly and securely. Qualifications Required Technical Skills • AI & Agentic Systems: Proven experience building applications with modern AI architectures, advanced prompt engineering, and multi-agent orchestration frameworks. • Model Management: Hands-on experience configuring, optimizing, and deploying diverse machine learning and language models. • Data Processing & Analysis: Strong proficiency in Python and data analysis libraries to manipulate, clean, and extract insights from high-velocity data streams. • Security Awareness: Familiarity with cybersecurity concepts, threat detection principles, or common security data formats (such as system logs, event tracking, or endpoint telemetry). Preferred Qualifications & Advantages • SLM & Local Deployment: Direct experience working with, optimizing, and deploying Small Language Models (SLMs) to run efficiently in local or resource-constrained environments. • Analytical Thinker: Exceptional problem-solving skills with the ability to diagnose complex system behaviors and iteratively improve AI model performance based on data. • Adaptability: Passion for staying at the absolute forefront of rapidly evolving AI technologies and applying them creatively to complex domains. • Experience: 3+ years of professional experience in data science, AI engineering, or related technical fields, with a proven track record of deploying AI-driven solutions. • Education: Bachelor’s degree in Computer Science, Data Science, Cybersecurity, or a related quantitative field (or equivalent practical experience) from a recognized and accredited university.

Realize your potential by joining the leading performance-driven advertising company! As a Senior GenAI Engineer in our GenAI team in the Tel Aviv office, you’ll play a key role in developing and enhancing our generative AI products, building advanced algorithmic solutions that improve content discovery, personalization, and monetization at scale. To thrive in this role, you’ll need: • M.Sc. in Computer Science, Mathematics, Engineering, or a related field • Strong Python, SQL and Spark skills • Familiarity with statistical modeling techniques • 2+ years of hands-on experience designing, building and evaluating GenAI workflows, including Agentic RAG, Tool calls evaluation, LLM-as-a-judge, RLHF, and LLM fine-tuning • 3+ years of experience in data science, analytics, and visualization • Excellent problem-solving and critical-thinking abilities • 3+ years of hands-on experience developing traditional machine learning algorithms, and NLP models. Bonus points if you have: • Strong mentoring and public-speaking skills, with a passion for writing research papers and technical documentation and sharing knowledge at conferences. • Experienced in Java or Scala How you’ll make an impact: • Be responsible for the entire algorithmic lifecycle of our user facing multilingual GenAI product at scale DeeperDive: data analytics, offline and online evaluation of new LLMs, evaluate the quality of our generative content, minimize hallucinations, evaluate guardrails, tool use and router calls, and improve retrieval combined with NER. • Improve personalized monetization flows and impact directly on the company’s revenue. • Work on a daily basis with on prem LLMs hosted in our datacenters, cooperate with external providers and embrace SOTA technologies. • Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems • Influence directly on the way billions of people discover the internet. • Work on projects such as DeeperDive, LLM monetization, Personalized user questions, organic recommendations and personalized ads. Our tech stack: Python, Java, Langfuse, TensorFlow, Spark, Kafka, Cassandra, HDFS, iceberg, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker. Why Taboola? If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about: • Adam Singolda, Taboola Founder and CEO: “You can copy anything from another business but you can’t copy a company’s culture.” • Well-being: Competitive benefits and well-being programs tailored to the region, including comprehensive health benefits, a fully stocked kitchen, and location-specific perks. • Flexibility: We offer a hybrid work schedule with 3 days in-office, with an option to come in more often if desired. • Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia. Ready to realize your potential? Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need. Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog. About Taboola Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale. About DeeperDive DeeperDive is a 10M monthly active users RAG based generative AI answer engine designed specifically for trusted publishers. It delivers concise, real-time answers that reflect what audiences are actively reading - surfacing not only what happened, but why it matters. Built on Taboola’s “Pulse of the Internet” - insights from over 600 million daily users — DeeperDive helps publishers respond to trending questions and deliver meaningful context on the topics their readers care about most. Rather than replacing journalism, DeeperDive enhances it. It empowers newsrooms to produce credible, nuanced content at scale, while preserving each publisher’s unique editorial voice and brand integrity. #LI-DN1 #LI-Hybrid