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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.
Role located in Ramat HaChayal, Tel Aviv.

Were looking for an enthusiastic and highly motivated Technical Support Engineer to identify, diagnose and resolve customers issues. The Technical Support Engineer will be a part of our Professional Services team.
This is an exciting opportunity to work in a challenging, fast-paced environment in a high-performance team. Here, we truly put our people first. We strongly believe in teamwork, and we encourage and trust our people to reach higher, learn more, and live up to their potential.
Job Description:
Taking ownership of customer issues reported by customers and prioritizing them based on urgency and importance
Researching, diagnosing, troubleshooting issues and identifying solutions to resolve system issues
Coordinating support case resolution with the appropriate internal teams: Sales, Professional Services, Product
Following standard procedures for proper escalation of critical or unresolved issues,

At Infinidat, a Lenovo company, we empower enterprises and service providers with cutting-edge storage platforms that redefine performance, reliability, and cyber resilience at scale. We're looking for an experienced Product Manager to assist with the strategy and roadmap for key areas of Infinidat's storage portfolio. At this role, you will work closely with R&D, customers, and go-to-market teams to translate enterprise requirements into product capabilities.

Responsibilities:

* Own the product roadmap and backlog for an assigned area of the InfiniBox/InfuzeOS portfolio.
* Gather and prioritize requirements from enterprise customers, Fortune 500 accounts, and field/sales teams, understand pain points and translate business needs into product and feature improvements.
* Write PRDs and detailed feature specifications for engineering, and confirm key requirements are met using hands-on validation.
* Partner with R&D on release planning, scoping, and prioritization trade-offs.
* Develop and maintain supporting documentation and best practices guides for the product area(s) owned, including deployment/configuration guidance, technical reference material, and internal enablement content for sales, support, and professional services.
* Support pre-sales, competitive positioning, and customer/analyst conversations.
* Track storage industry and market trends (AI/data workloads, cyber resilience, hybrid cloud, file and block) to inform strategy.
* Collaborate cross-functionally with marketing, sales engineering, professional services, and support organizations.

DealHub.AI is building the future of agentic revenue technology. Trusted by leading global businesses, we’re redefining what revenue teams can achieve with AI and agentic execution across the deal lifecycle. Our mission is simple: help businesses Own Your Revenue with greater speed, intelligence, and governance. As an Solution Expert you will serve as the technical trusted advisor for our customers, bridging AI capabilities with their specific business goals and revenue workflows You will embed deeply with customers. Part consultant, part engineer, part strategic advisor: leading AI sessions, configuring AI-driven workflows using DealHub MCP, training users on best practices, and ensuring measurable business outcomes. You'll collaborate closely with Customer Success, Product, Support, and Engineering teams, and will be the go-to expert for any AI-related technical solution. This is an ideal role for someone who thrives at the intersection of cutting-edge AI technology and real-world business challenges. This role is ideal for someone who thrives on ambiguity, moves fast, and finds equal satisfaction in writing clean code and presenting a solution to a CFO. Key Responsibilities
* Embed deeply with customers to understand their technical environment, business processes, and AI workflows and then design and build solutions that fit.
* Build and deploy AI-powered workflows, MCP-based automations, and intelligent features within the DealHub platform tailored to each customer's use case taking into account the integration landscape such as Salesforce, HubSpot, Dynamics, NetSuite, and billing platforms.
* Leverage LLM, AI, APIs, webhooks, data pipelines, automation scripts.
* Lead technical AI sessions — review requirements, demo solutions, help build agents and perform training.
* Translate complex AI and technical concepts into clear, tangible business value; operate as a trusted advisor, not just an implementer.
* Identify and resolve technical blockers proactively; operate with confidence under ambiguity and incomplete information.
* Build reusable engineering assets: integration libraries, prompt templates, and AI workflow scaffolding that scale across the customer base.
* Act as a direct feedback loop from the field to the Product and Engineering teams surfacing patterns, edge cases, and AI feature opportunities discovered during deployments.
* Monitor post-go-live and drive continuous improvement.

Were looking for a Data Scientist to join our R&D department!
Why is this role so important?
A data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights.
So, what will you be doing all day?
Your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.

Were looking for a sharp and driven Data Analyst to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day to day of a Big Data Analyst Customer Facing (Data Labs) at Similarweb look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using Similarwebs raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.

Were looking for a Product Analyst to join our team and act as a central pillar between our data, our product, and our business strategy.
This isnt a role for someone who just wants to answer tickets. You will be embedded with Product Managers and Growth leaders to not only provide data but to help shape the roadmap and influence how we build, launch, and monetize our products. We are looking for an analyst with a "business partner" mindset, someone who can look at a dataset and see the commercial opportunity or the user friction point before others do.
What Youll Do
Strategic Partnership: Work alongside PMs and leadership to define success metrics for new features and long-term growth initiatives.
Full-Funnel Ownership: Design and measure KPIs across the entire user journey, from initial activation to complex monetization and retention loops.
Proactive Discovery: Conduct deep-dives to uncover hidden bottlenecks. You won't just report on what happened; you'll recommend what we should do next.
Narrative Building: Translate complex technical data into clear, "bottom-line first" narratives that drive action across the company.
Cross-Functional Support: Act as the analytical bridge, supporting multiple product domains and ensuring a consistent, data-driven approach to every decision.

Were looking for an Infrastructure Data Engineer to join our Data Labs (DL) department, which specializes in professional services for our super-premium customers. This role will report to our DL (Datalabs) Infrastructure Team Manager in the R&D.
Why is this role so important?
A data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As a Data Infrastructure Engineer in the Datalabs group, you will be the technical backbone supporting our data production, analyst, and data science teams. You will own and maintain our AWS cloud accounts and Databricks workspaces, optimize pipeline executions, and proactively modernize our tech stack to reduce tech debt - ensuring our platform remains scalable, reliable, fast, and cost-effective.
Given the business-oriented nature of Datalabs, you will work closely with cross-functional stakeholders and internal teams who interface directly with strategic customers. By unblocking operational bottlenecks and building robust tooling, you will empower our analysts and data scientists to deliver custom, high-value data products to our customers seamlessly.
So, what will you be doing all day?
Environment & Workspace Management: Administering and optimizing our groups AWS cloud accounts, IAM policies, and Databricks workspaces to ensure peak performance, rock-solid security, and cost efficiency.
Execution & Pipeline Infrastructure: Owning the health, reliability, and scaling of our core data execution environments (Airflow, Docker, EKS/ECS, distributed queues, and database engines).
Tech Debt Modernization: Proactively researching, benchmarking, and replacing legacy debt with modern technologies to keep our platform fast and cutting-edge.
Developer & Production Support: Serving as the technical focal point for internal analysts and data science teams-providing the tooling, standards, and infra support they need to build custom client reports smoothly.
Cross-Group & Client Alignment: Partnering with external engineering teams and internal stakeholders to support custom data delivery pipelines and uphold high-priority customer SLAs.