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We're looking for a Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of our companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across our company to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across all of our company.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our company's next-generation data stack.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools
In this role you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals.

Were looking for a senior-level backend engineer to join our growing Engineering team in TLV.
This role will require you to bring features to the finish line while collaborating closely with other developers, as well as with the Product, QA, Data, and Machine Learning teams-all with the goal of delivering a seamless, joyful experience for our customers.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Help build our products using microservices written in Typescript (using NestJS).
Leverage our in-house autonomous tools to manage all development flow, from setting up our development environment to creating git branches and deploying services to production
Collaborate closely with the Product team, in a self-sufficient squad to achieve the squads OKRs
Be the owner of your domain to ensure code quality, performance, and scalability of our products
Coach and mentor other developers and help them elevate their skills.

Anyone can ship an AI agent. Shipping one thats right ~98% of the time, with no human checking its work, takes different engineering. Thats what this team builds.
We're looking for a Senior Backend Engineer to help push our AI customer-service agents closer to fully autonomous insurance service. You'd be joining the team behind the agent that talks to real customers every day over email, phone, chat, and SMS - handling policy questions, claims conversations, and verified documents end-to-end, with no human in the loop. This isn't a demo or a copilot. Real customers, real money, real stakes, every day.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design, build, and own production LLM agent systems end-to-end - deciding how the agent thinks, what it's allowed to do, and how it fails safely
Work on our real-time voice agent, where the hard problems are conversational: interruptions, mid-sentence tool calls, and keeping response times imperceptibly fast
Shape the next generation of our knowledge base - how the agent's knowledge is structured, curated, and served, so answers stay grounded as coverage grows
Ship changes as controlled experiments, measure them against thousands of replayed real conversations on our in-house eval platform, and graduate winners into production
Track cost per conversation across millions of LLM calls and find the wins that cut spend without cutting quality
Own what the model knows and says - the customer context it sees, the limits on what it may reveal, and the guardrails against confident nonsense
Build and operate scalable backend services in TypeScript/Node on Kubernetes/AWS with deep observability - if you ship it, you own it.

We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

We're looking for a Senior Backend Engineer to help build and scale the Machine Learning Platform that powers how our company uses AI across the business. You'll be part of the ML Platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
We believe three things matter for every role at our company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work. Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Design and build the foundational ML platform and AI agents to accelerate data science model delivery across all business units
Architect cloud-native microservices running on Kubernetes, using infrastructure-as-code to automate model deployment and management
Own the end-to-end ML lifecycle, covering training, testing, deployment, and real-time monitoring
Evaluate and choose the right tools and technologies based on workload demands and performance requirements
Collaborate with engineering, data science, and product teams to keep ML projects aligned with business goals
Identify and fix reliability, scalability, and performance gaps before they become problems.

We are seeking a motivated and hands-on Technical Trainer or Customer Enablement Specialist with experience delivering customer and partner training in SaaS environments. The ideal candidate is passionate about helping users adopt new technologies, creating effective learning materials, and delivering engaging training experiences.
In this role, you will own the end-to-end training ecosystem for our Meeting Insights, including course development, training delivery, certification programs, and learning resources. You will work cross-functionally with Product, Customer Success, R&D, and Business teams at HQ and globally to ensure customers, partners, and internal stakeholders are fully equipped to succeed with our platform.
What You Will Gain:
Hands-on experience with cutting-edge Conversational AI technologies in real enterprise environments
A key role in supporting customer adoption and success through effective training and enablement programs.
Deep exposure to both technical and business domains through close collaboration with Product, R&D, and customer-facing teams
Opportunities to grow your expertise in AI, SaaS, and customer enablement, with strong potential for career advancement
The ability to influence product adoption and customer success at scale
Contribution to an award-winning solution, recognized as the Best Use of AI at the UC Awards 2024
About Us:
We bring over 30 years of expertise in enterprise voice services, with a strong track record of innovation in Conversational AI SaaS applications. Our Voice.AI platform powers workplace transformation for more than 50 Fortune 100 enterprises, enabling smarter, AI-driven collaboration.
Meeting Insights, launched in early 2024, has rapidly gained traction with hundreds of customers and POCs. We are now entering an exciting new phase of growth and product evolution.
We are an open, inclusive, and diverse organization where employees are at the heart of everything we build. We offer a flexible, collaborative environment and meaningful opportunities for career growth.
Your mission:
Own and execute the design, development, and delivery of training programs, courses, and certification tracks for Meeting Insights.
Build and maintain a comprehensive knowledge base for internal teams (sales engineers, support, customer success), partners, and customers
Collaborate with Professional Services, partners, and customers worldwide to identify and address training needs
Work closely with Product Management, Technical Writing, and Marketing to develop high-quality onboarding and training materials
Design and deliver hands-on, technical training sessions (virtual and/or in-person)
Continuously improve training effectiveness באמצעות feedback, analytics, and evolving product capabilities.

Through innovative technology and AI-driven solutions, our company is reshaping the eyewear industry and delivering a seamless, personalized shopping experience. We ensure quality, affordability, and efficiency by controlling the full supply chain, from product design and manufacturing to optical lens production and digital experience.
Our Customer Experience team is looking for an experienced & driven CX Technical Project Manager. This position will report to the VP of Customer Experience.
What Youll Do:
Own, manage, and optimize the CX tech stack, tools, and platforms.
Build, improve, and maintain CX workflows, processes, and SOPs.
Monitor operational backlogs, bugs, and ongoing technical tasks.
Design and implement tools to improve CX speed, quality, and efficiency.
Maintain dashboards, reports, and performance analytics to support business decisions.
Lead A/B testing initiatives across all support channels and deliver insights to leadership.
Manage onboarding/offboarding of CX systems and ensure smooth platform operations.
Handle DSR processes, vendor invoices, and operational tracking.
Analyze CX performance, forecasting, and interaction volumes across channels.
Maintain IVR systems and support global support-site operations.
Collaborate with Product and leadership teams on CX roadmap initiatives.
Continuously identify and remove operational bottlenecks to improve customer experience.

We are seeking an experienced Software Architect to lead the technical vision and architectural strategy of our cloud-native SaaS platform. Our team develops an Azure-based platform for building AI agents and integrating them with telephony and voice communication systems, enabling intelligent, real-time customer interactions at scale.
Our platform is built on a large-scale, distributed microservices architecture powered primarily by Node.js and deployed on Kubernetes. The technology stack includes Docker, Terraform, Azure cloud services, and advanced AI technologies such as Large Language Models (LLMs), Text-to-Speech (TTS), and Speech-to-Text (STT) services.
The ideal candidate combines deep software architecture expertise with strong hands-on engineering capabilities. They bring a proven background in cloud-native platforms, distributed systems, modern DevOps practices, and AI-driven application development. Comfortable operating across architecture, infrastructure, and implementation layers, they thrive on solving complex technical challenges.
Responsibilities:
Define and evolve the overall system architecture and technical roadmap.
Drive architectural decisions that ensure scalability, reliability, security, and performance.
Establish engineering standards, best practices, and design principles across development teams.
Provide technical leadership and mentorship to engineering teams throughout the software development lifecycle.
Collaborate closely with product, engineering, and operations teams to deliver high-quality solutions.
Participate hands-on in architecture reviews, system design, code reviews, troubleshooting, and performance optimization.
Lead cloud-native and DevOps initiatives, ensuring efficient deployment, monitoring, and operational excellence.
Promote and leverage AI-assisted development tools and practices to improve engineering productivity, code quality, and delivery velocity.

We are looking for a Service Reliability Engineer to support our enterprise-grade SaaS Meeting Intelligence solution, working closely with enterprise customers, partners, and internal teams to deliver measurable value.
You will join a dynamic R&D group developing AI-powered UC recording SaaS solutions, and provide expert support for complex production issues in collaboration with field engineers, R&D, and customers.
This is a hands-on role requiring strong troubleshooting skills, a passion for learning new technologies, and ownership of service reliability and quality.
The position is based in Israel, as part of a global SRE team with members in the USA and Israel.
Your mission:
Investigate, troubleshoot, and resolve complex production issues and escalations
Monitor production systems and proactively identify potential reliability risks
Participate in a 24/7 on-call rotation to support critical incidents
Work closely with R&D, QA, PM, CSM, and other teams to resolve issues and improve system reliability
Collaborate directly with customers on technical escalations on a regular basis
Analyze incidents, perform root cause analysis, and contribute to post-incident reviews
Follow and contribute to troubleshooting protocols and best practices
Maintain and improve monitoring, alerting, and observability tools
Create and maintain internal environments for testing and troubleshooting
Document solutions and contribute to internal and customer-facing knowledge bases
Support training activities for service teams when required.

Appdome's mission is to protect every mobile app in the world and the people who use them. We are the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps — with no SDKs, no coding, and no disruption to engineering cycles.
Our platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities, powered by deep learning models trained on a decade of mobile defense data and trillions of live threat events. From build time to runtime, Appdome's AI Agents help mobile brands detect, investigate, and respond to threats faster than ever — recognized as the best AI Platform for Cyber Resilience at RSA Conference 2026 for the second consecutive year. Leading financial, healthcare, m-commerce, and B2B brands rely on Appdome to secure over 50,000 mobile apps and protect more than 1 billion end users globally.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.
?About the Role
We are looking for a Data Assurance Engineer with strong experience in data validation, automation, analytics testing, and large-scale event pipeline quality.
This role is focused on ensuring the accuracy, stability, and reliability of data across our analytics and security event systems. The ideal candidate will be responsible for building automated validations, investigating data discrepancies, monitoring data quality, and working closely with engineering, data, and product teams.
Responsibilities

* Design, build, and maintain automated validation processes for large-scale event pipelines.
* Validate end-to-end data flows across ingestion, processing, storage, and dashboard layers.
* Create SQL-based validations to verify event counts, unique devices, metadata accuracy, schema
* consistency, latency, and data freshness.
* Investigate discrepancies between production systems, staging environments, data warehouses, object
* storage, and customer-facing dashboards.
* Monitor event volume, data latency, anomalies, spikes, drops, duplicates, and missing data.
* Build and maintain CI/CD validation jobs using tools such as Jenkins or GitLab CI.
* Create clear automated reports, dashboards, and email summaries for validation results.
* Work closely with backend engineers, data engineers, QA teams, and product stakeholders to identify,
* report, and validate fixes for data quality issues.
* Support performance and scalability testing for analytics dashboards, queries, and data pipelines.
* Help improve internal data assurance processes, data observability, and production monitoring.

we are where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner, we deliver hands-on DevOps and FinOps and GenAI support that drives real results.
We work across EMEA, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.
In this position, you will be a key member in the pre-sales process, working directly with global startup customers and cross-functioning with account managers to develop AWS solutions for the customers.
Work location: hybrid from Tel-Aviv
Curious about what it's really like to work at our company?
Explore our benefits, culture, and what success in your first year could look like here.
If you are interested in this opportunity, please submit your CV in English.
Key Responsibilities
Meet with customers, understand their business challenges, and design AWS solutions that address them, covering architecture, cost-efficiency, scalability, and security through Statements of Work (SOW)
Analyze existing customer AWS architectures and propose improvement roadmaps
Collaborate cross-team with different departments to ensure solutions are designed according to AWS best practices
Build thought leadership in the cloud community by contributing to blogs, workshops, webinars, conferences, and more, representing our company as a trusted voice in the ecosystem
Travel both locally (to meet with customers, partners, and attend local events) and abroad (at least once a quarter).

Were looking for a Senior Data & Analytics Architect to join our team and work directly with startup CTOs, engineering teams, and account teams. This is a hands-on, customer-facing architecture role where you will design and deliver production-grade data platforms on AWS.
The role is focused on turning real business problems into working systems, from early discovery and architecture design to supporting implementation. This is not a pure strategy or management role, its about making clear technical decisions and ensuring they hold up in production.
Work location: hybrid from Tel Aviv
Curious about what it's really like to work at our company?
Explore our benefits, culture, and what success in your first year could look like here.
If you are interested in this opportunity, please submit your CV in English.
Key Responsibilities
Design and deliver end-to-end data platforms on AWS, covering ingestion, storage, processing, and serving layers, including Well-Architected reviews and contribution to SOWs and HLDs
Work directly with startup customers to understand requirements, challenge assumptions, and shape practical solutions
Lead technical discussions, workshops, architecture reviews, and POCs
Translate ideas and early concepts into clear architectures, including HLDs, SOWs, and implementation direction
Make and explain trade-offs across cost, performance, scalability, and complexity
Stay close to delivery, supporting teams to ensure solutions are implemented correctly
Collaborate with Data Engineers, DevOps, Solution Architects and Account Managers to move projects from concept to production
Contribute to internal standards, reusable patterns, and reference architectures
Operate in a fast-paced, project-based environment with multiple customer engagements
Stay up to date with modern Data Engineering and Analytics practices, and contribute to internal enablement, patterns, and knowledge sharing
Work in a customer-facing environment that includes occasional travel, both locally for meetings and events, and internationally around once per quarter.