Founding Engineer, AI Platform

Remotebase

19h

About The Position

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.

Requirements

You are an entrepreneurial builder who has experienced a 0-to-1 journey, ideally as a founder, founding engineer, or early employee at a startup.
You have built something meaningful from a blank page and can point to decisions, tradeoffs, and outcomes that were truly yours.
You have strong full-stack judgment and move comfortably between product UI, backend APIs, data models, infrastructure, and customer needs.
You enjoy ambiguous product and platform problems where the right solution or abstraction is not obvious on day one.
You care deeply about solving customer pain, not just producing technically elegant systems.
You have shipped AI-powered product features in production, or have unusually strong evidence that you can learn and build in this space quickly.
You balance speed with durability. You know when to prototype, when to generalize, and when to revisit an early decision.
You have high agency, low ego, strong product instincts, and a bias toward action.
You communicate clearly with both technical and nontechnical teammates and are comfortable working directly with customers.
You use AI tools to accelerate your work without outsourcing your judgment to them.
You are excited by agents, RAG, tool calling, evals, and the edge cases that emerge when these systems interact with real businesses.

Nice To Haves

Experience with Python, TypeScript, React, Postgres, Celery or other background job systems, AWS, or comparable technologies.
Experience building integrations with Gmail, Slack, Google Calendar, CRMs, document systems, or other enterprise APIs.
Experience with LLM evals, observability, retrieval, agent orchestration, prompt reliability, or tool-use reliability.
Experience designing secure, multi-tenant enterprise software with thoughtful permissions and data access controls.
Strong product taste and the ability to make early or internal tools feel coherent, intuitive, and trustworthy.

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.