Engineer

About Ember AI
Ember AI is building Enterprise Intelligence: an AI-native workspace that turns a company's meetings, email, documents, Slack, and operational systems into durable memory, proactive agents, and customer-specific workflows.
We are looking for an entrepreneurial, product-minded full-stack engineer to join our founding team and help turn early customer pull into a durable platform. This is a true 0-to-1 role. You will work across product, infrastructure, agents, evals, connectors, and customer workflows, often moving from an ambiguous customer problem to a shipped product experience.
The ideal candidate has lived the 0-to-1 journey before, whether as a founder, founding engineer, or early technical hire. You know how to make progress with limited scaffolding, talk directly with users, make smart tradeoffs, and build systems that can evolve beyond the first customer or use case.
We are building a real product, not a demo, a chatbot wrapper, or a collection of bespoke one-offs. The right person can create reusable technical primitives, sweat the user experience, and ship quickly in a messy, fast-moving environment.
We care more about slope, judgment, and evidence of exceptional building than a specific number of years. This will likely be a strong fit for someone with roughly 2–7 years of experience, or equivalent experience building a company or product from the ground up.

Key Responsibilities

• Own meaningful product areas end to end, from customer discovery and technical design through implementation, launch, and iteration.
• Build core Enterprise Intelligence surfaces, including the agent builder, brain pages, connectors, source transparency, calendar and meeting workflows, and the internal tools we use every day.
• Design reusable platform primitives for agents, including triggers, tools, approvals, evals, memory, observability, and workflow execution.
• Turn messy, customer-specific workflows into reliable and extensible product experiences.
• Work across the stack using React, TypeScript, Python, FastAPI, Postgres, background jobs, cloud infrastructure, LLM APIs, and retrieval systems.
• Build for production from the start, including tenant isolation, reliability, monitoring, permissions, data security, and secure connector access.
• Work directly with customers through discovery calls, workflow reviews, debugging sessions, implementation, and launch support.
• Use AI coding tools aggressively and thoughtfully while maintaining strong engineering judgment and building systems others can understand, operate, and extend.
• Help shape the product roadmap, technical architecture, engineering practices, and culture of an early-stage company.