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As our Senior Software Engineer, you will design and develop complex high-performance, high-quality software, spanning across algorithms, application logic, and infrastructure.

Our system is built in a microservice architecture that interacts with external systems (such as the blockchain and our partners systems) and meets demanding performance, resilience, and security requirements. The code is written mostly in Python and in C++ and utilizes continuous delivery and automated testing methodologies.

Were looking for a Corporate Controller - Group Lead to manage our HQ parent company and subsidiaries accounting and financial aspects. This role will report to the companys Director of Finance.
Why is this role so important at our company?
The Corporate Controller will play a major role and will hold all responsibilities related to month and quarter closing processes as well as any other financial/accounting operations for HQ.
So, what will you be doing all day?
Your role as part of the Controllership team means your daily responsibilities may include:
Lead the monthly, quarterly and annual closing process of global subsidiaries and parent company, including preparation of journal entries and flux analysis
Lead a significant part of the annual 20-F filling and other relevant fillings
Lead a team of direct reports
Participation and support of audit process with auditors including the provision of WPs as required for quarterly reviews and annual audit
Preparation of annual tax returns and other statutory reporting requirements
Prepare and engage in analysis of complex tax issues with outside advisors
Assist in design and documentation of internal controls (SOX) and policies
Support the implementation of new accounting standards in order to comply with US-GAAP
Support the work of AP team to ensure accuracy of financial records
Supporting billing-related processes and integration with financial systems
Participate and lead improvements in internal financial and system processes.

The marketing world is undergoing its biggest shift in a decade. Discovery is no longer just "search"-it's increasingly mediated by AI. Users are asking questions in ChatGPT, Perplexity, and Google AI Overviews, and the traditional "search → click → website" funnel is fragmenting. This shift has created a new discipline: Generative Engine Optimization (GEO) and AI Engine Optimization (AEO).
we are uniquely positioned to lead this space. We have proprietary data that reveals not just what AI shows users, but what users actually do next-which channels they visit, where demand flows, and how brands win (or leak) visibility. Our mission is to help marketers understand their visibility in AI platforms, connect that visibility to downstream business outcomes, and take action to improve.
The Impact of This Role
As a Product Manager for our GenAI team*, you will own the data backbone of Gen AI Intelligence. You'll need to be sharp on how to combine, utilize, and analyze diverse data sources** to answer the questions our customers need answered.
You'll work at the intersection of our Data Science team, Data Engineering team, and Platform team-turning raw data assets into user-facing products. But building the right products requires understanding the domain: you'll dig into SEO/GEO workflows, spend time with customers and design partners, and learn how marketing teams actually operate. The goal is to let user context drive your data decisions.
Your core mandate:
Own a product area end-to-end within Gen AI Intelligence-from the underlying data and pipelines, through the user-facing experiences, to how customers extract value via APIs and integrations.
Define what data we need, how we structure it, and how we expose it to users and downstream systems
Deeply understand user workflows and jobs-to-be-done to identify the highest-leverage data solutions
Partner with Data Science to translate models and extractions into usable, reliable data pipelines
Ensure data quality, coverage, and governance across our Gen AI data estate
Drive product development end-to-end: from discovery through definition, prototyping, design, development, and deployment-with continuous iteration
Collaborate across a multi-disciplinary team: data scientists, data engineers, full-stack developers, UX designers, product marketers, and business stakeholders.
What you'll do day-to-day
Obsess over user context: Understand how SEO practitioners, content marketers, and marketing leaders actually work-what questions they're trying to answer, what data would unlock value, and where current solutions fall short
Define data products end-to-end: From discovery through definition, schema design, pipeline development, and delivery-ensuring consistent quality and velocity
Connect data to user outcomes: Work closely with product teams that consume your data (reporting UX, recommendations, APIs) to ensure the data products actually solve user problems
Partner deeply with Data Science and Engineering: Translate DS models into production-ready data products; define requirements for data engineering pipelines; prioritize platform investments;
Define the core metrics, datasets, reports, and insights that will be made available to our users through our SaaS platform, APIs and MCPs.
Own data quality and coverage: Define metrics for data completeness, accuracy, and freshness; build feedback loops to continuously improve
Make tradeoffs with evidence: Use quantitative and qualitative analysis and user research to prioritize ruthlessly-not everything can be built, so you need to know what matters most.

We are looking for a Senior Product Manager to join our Sales Intelligence (SI) team. While our Sales Ops-focused teams build the "backbone" of sales strategy (B2B-heavy data and admin flows), this role is dedicated to the Sales Person. Your mission is to build the "B2C-style" front-end experience for individual sales professionals. You will create tools that aren't just powerful, but are a joy to use-making digital intelligence feel like a superpower in the hands of every salesperson. You will lead the strategy for how a seller finds, researches, and closes deals daily.
A day to day as a Product Manager means...
User-Centric Research: Conduct deep-dive interviews and observations with Sales Reps, Account Executives, and SDRs to understand their daily "hustle" and friction points.
B2C Mindset in a B2B World: Design and define features that feel like consumer-grade apps-fast, intuitive, and immediately actionable.
Product Vision & Strategy: Build and adjust the vision for "Sales Empowerment" tools, ensuring they align with our broader Sales Intelligence goals.
Cross-Functional Collaboration: Partner with big data engineers and data scientists to turn complex signals into simple "buying cues," while working with designers to ensure a seamless UI.
Rapid Iteration: Roll out features responsibly through beta programs, monitoring KPIs like "Daily Active Usage" and "Time-to-Value" for the individual seller.
AI for Sales: Define how AI can automate the "boring stuff" for sellers-from personalized outreach generation to automated prospect discovery.

As an AI Engineer at our company, you will be a key player in building our new AI platform, AI Studio. This platform aims to provide users with instant answers to complex market research questions, generate world-class reports, and create live, interactive, and powerful dashboards. Our goal is to reduce the complexity and time-to-insight for our users, helping them streamline their market tasks and achieve automation that drives real value.
So, what will you be doing all day?
Design and develop LLM-based intelligent agents that can handle complex market research queries.
Utilize LangGraph and other frameworks to create state of the art AI agents that integrate various tools and data sources.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with product, data, and UX teams to ensure that AI solutions are aligned with user needs and business goals.
Continuously evaluate and improve the performance of AI models to ensure high-quality and data-driven results.

Were looking for a 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) Data Science Team Manager in the R&D.
Why is this role so important at our company?
we are 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 and support a complex data model pipeline that helps 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 engineer in the Datalabs team, you will work on the very core of the company. Part of your role will be to create processes that help turn raw data into usable metrics and leverage AI models and statistical algorithms to support out-of-the-box requests from customers who want custom data labs. The Datalabs departments business-oriented nature also means you will be supporting a team of analysts and data scientists who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class data labs.
So, what will you be doing all day?
Building and maintaining our big-data pipelines
Take a major part in designing and implementing complex high-scale systems using a large variety of technologies
Be part of a team with smart and motivated engineers, and data scientists, to collaborate on the planning, development, and maintenance of our products
Implement solutions in the AWS cloud environment, and work in Databricks with PySpark.

Were looking for a Backend AI Engineer to own and build agentic AI architecture. This role sits at the intersection of backend engineering and production-grade AI systems. Youll design, build, and scale the backend that powers our AI creators, enabling intelligent, reliable, and observable agentic workflows at scale.
Youll work on orchestrating multi-step AI workflows that involve LLMs, tools, and decision logic, and ensure they operate reliably under high load and real-world usage. A key part of the role is designing systems that can handle non-deterministic AI behavior, recover gracefully from failures, and continue to perform as usage and complexity grow. Youll also be responsible for making architectural decisions that support scalability, low latency, and long-term maintainability of our AI platform.