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render.ai is Monday.com's new AI venture focused on redefining how humans use AI for work. The product enables anyone to bring ideas to life in minutes using natural language. The team operates as an autonomous, early-stage startup unit within a larger organization, with no fixed playbook—engineers actively shape the product direction, not just implement specifications.
This Senior Software Engineer role is for an experienced, product-minded engineer who will work across the full stack. Rather than receiving polished specs, you'll start from user needs, help define the product, and take solutions all the way to production. The role emphasizes using AI as leverage for judgment and productivity, not as a substitute for decision-making. You'll spend significant time deciding what should be built and validating that it's actually good, with AI handling a meaningful share of implementation work.
You'll be deeply hands-on, building end-to-end solutions. The ideal candidate thinks like a product builder, cares about UX, challenges assumptions, and iterates based on user feedback. You'll have a real say in what gets built, not just how it's built. Strong communication and collaborative problem-solving are essential in this small team environment where priorities shift and many important problems remain undefined.
The role values engineers who thrive in early-stage startup conditions, create clarity from ambiguity, and move quickly without sacrificing quality. You'll work across the full technology stack, with the ability to move from frontend to backend to infrastructure as needed.
REQUIREMENTS:
- ~4+ years of software engineering experience
- Deeply hands-on with React/Next.js, Node.js, and TypeScript
- Comfortable with cloud infrastructure (GCP/AWS), CI/CD, and production systems
- Strong product taste and user empathy
- Excellent communication skills and collaborative mindset
- Ability to build end-to-end solutions and move across the stack
ADVANTAGES:
- Experience building AI-native products
- Familiarity with modern AI/LLM tools used day-to-day
- Experience with vector embeddings, RAG architectures, or AI inference pipelines
- Experience with real-time collaboration, WebSockets, or state-sync frameworks
- Background in SaaS, cybersecurity, infrastructure, or hardware
