Senior AI Software Engineer- Work Experience

About monday.com

About the team:
The Workspace & Layout team is part of the Work Experience group within monday.com's Human Agent Collaboration department. We own the core workspace product — the visual environment where users organize, navigate, and interact with everything inside monday.com — from layout and structure to the evolving workspace agent experience. We sit at the intersection of foundational infrastructure and end-user delight, shipping features that touch every monday.com customer.

About the role:

• Build new AI-native products and features from 0→1, iterating rapidly based on user feedback
• Work across the stack using modern technologies to create delightful user experiences
• Lead and participate in architectural decisions as we scale multiple new product lines
• Take full ownership of features from design to implementation, deployment, and monitoring
• Partner closely with product and design to shape user workflows and accelerate delivery
• Drive engineering excellence, reliability, and performance across fast-moving codebases
• Help define best practices for AI-powered product development at monday.com

Requirements:

• 5+ years of professional software engineering experience, with demonstrated strong technical skills building full-stack applications end-to-end
• Deep knowledge of React (Next.js), Node.js, and TypeScript
• Experience building features that integrate LLMs or other AI technologies (e.g., OpenAI, Gemini, Claude, Llama)
• Experience with testing frameworks (Jest, Playwright, Cypress, etc.)
• Experience working with cloud infrastructure (GCP/AWS), CI/CD, deployments, and monitoring
• Familiarity with performance optimization and scalability across frontend and backend
• Strong communication skills, team mindset, and empathy
• Passion for creating user-centered products that customers rely on daily

Nice-to-have:

• Hands-on experience building LLM flows and writing evals to validate model behavior — you know what "good" looks like and can measure it
• Experience with vector embeddings, RAG architectures
• Familiarity with product discovery, rapid prototyping, or startup environments

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