Founding Engineer, AI Platform
Ember AIUSA4d ago
AIEngineeringPlatformremotecurated-jd
Job description
Founding Engineer, AI Platform at Ember AI.
About the role
Ember AI is developing an enterprise intelligence workspace that transforms internal communications and operational data into proactive agents and durable workflows. We are seeking a product-focused engineer to join our founding team and lead the transition from initial customer demand to a scalable platform.
Key facts
What you'll do
- Manage product features from initial discovery and technical architecture through to final deployment.
- Develop core surfaces including agent builders, brain pages, data connectors, and meeting workflows.
- Create reusable platform primitives for agent memory, observability, evaluation, and workflow execution.
- Convert bespoke customer requirements into extensible, reliable product features.
- Build production-ready systems with a focus on tenant isolation, security, permissions, and monitoring.
- Engage directly with customers to debug issues, review workflows, and support product launches.
- Influence the technical roadmap, engineering culture, and architectural standards of the company.
Requirements
- Roughly 2 to 7 years of professional experience, or equivalent history building products from the ground up.
- Proven track record as a founder, founding engineer, or early technical hire in a startup environment.
- Ability to navigate ambiguous problems and make independent technical and product tradeoffs.
- Experience building and shipping AI-powered features for production environments.
- Proficiency in full-stack development and a willingness to work across the entire stack.
- High agency and a strong bias toward action with the ability to communicate with both technical and non-technical stakeholders.
Nice to have
- Proficiency with Python, TypeScript, React, Postgres, and background job systems like Celery.
- Experience with cloud infrastructure such as AWS.
- Background in building integrations with enterprise tools like Slack, Gmail, Google Calendar, or CRMs.
- Expertise in agent orchestration, RAG, LLM evaluations, prompt reliability, and tool-use reliability.
- Experience designing multi-tenant enterprise software with complex data access controls.
- Strong product design sense for creating intuitive internal and customer-facing tools.
Skills & tools
- React, TypeScript, Python, FastAPI, Postgres, background job systems, cloud infrastructure, LLM APIs, and retrieval systems.
Practical notes
- Success in the first 30 days involves identifying reliability gaps and shipping improvements.
- By 60 days, you will own a core platform primitive or agent workflow.
- By 90 days, you will independently lead a customer-facing workflow or major product surface.