BI and AI Solution Engineer

We are monday.com, a global software company transforming how businesses run. Our product suite can adapt to the needs of diverse industries and use cases within one powerful platform, empowering ~245,000 customers worldwide to reimagine how work gets done, drive greater efficiency, and scale like never before. With over 2,500 employees across the globe, we grow by prioritizing transparency and knowledge sharing. We care about the impact you make, not the hours you clock, so we encourage initiative, ownership, and fresh thinking. We back our people with flexible work, wellness and mental health support, and a work environment built on collaboration. We are looking for an innovation-driven pioneer to lead the most ambitious transformation in our data history. This is not a traditional BI role; it is a call to architect the "brain" of our organization. You will be responsible for implementing cutting-edge GenAI solutions and tools that dramatically improve team efficiency, support true user self-service, and provide deep insights easily, automatically, and quickly. Listen to our podcast here: https://podcasts.apple.com/il/podcast/startup-for-startup/id1404411941?i=1000766148682 See some more here: https://www.youtube.com/watch?v=x-m0ag0cty0 https://engineering.monday.com/meet-the-geniuses-behind-our-bi-tool-bigbrain/

Requirements: 6+ years of experience as a BI Developer or Data Engineer with a heavy focus on DWH design, dimensional modeling, and architecting complex data ecosystems. AI Implementation: Hands-on experience implementing AI or automation within BI and analytics processes to drive operational efficiency. Modern Dev Stack: Hands-on experience with AI-native development environments such as Claude, Cursor , or similar tools to accelerate delivery. Expert Technical Stack: Mastery of SQL and deep hands-on experience with Snowflake , Airflow , and dbt . Strategic Partnership: Ability to partner with stakeholders and internal teams to translate complex business requirements into LLM-powered workflows . Quality & Governance: Experience building structured evaluation plans to test workflows against rigorous accuracy, reliability, and compliance standards. Architectural Vision: Deep understanding of Semantic Layers —knowing how to centralize business logic so it remains consistent across all platforms. Passion for LLMs: A fast-learning mindset with a genuine desire to build innovative, category-defining AI-driven products and act as an advocate for best practices in LLM development. Advantages Scripting Mastery: Strong proficiency in Python or other scripting languages for data manipulation, API integration, and AI automation. AI Architecture: Hands-on experience with RAG , LangChain, LlamaIndex, or Vector DBs. Orchestration: Advanced proficiency in Airflow and automated workflow tools. Production Excellence: Experience deploying AI/Data products in high-scale production environments with CI/CD. Data Security: Practical implementation of RLS, RBAC, and OAuth within AI-to-Data layers. Unstructured Data: Building pipelines for non-tabular data (PDFs, Slack, CRM notes).