ekai

About the Company

Every meeting is packed with critical discussions and decisions, but the real work often begins afterward — chasing updates, tracking action items, and answering the same questions over and over. Ekai changes that. It listens, remembers, and helps you move things forward without the extra hassle. Imagine a teammate who drafts updates, summarizes key decisions, reminds you of your action items and respond to repeated query on your behalf — so nothing ever slips through the cracks again.

Listed Jobs

Company Name

ekai

Job Title

Full Stack AI Engineer

Job Description

**Job Title:** Full Stack AI Engineer **Role Summary:** Founding‑team engineer responsible for designing, building, and deploying end‑to‑end AI‑native solutions. Owns front‑end, back‑end, and AI layers, focusing on multi‑step reasoning agents, long‑term memory, and production‑grade Retrieval‑Augmented Generation (RAG) pipelines. **Expectations:** * Deliver high‑quality code in an agile, low‑bureaucracy environment. * Own complete feature lifecycles from concept to production. * Balance rapid iteration with maintainability and performance. * Act as a generalist; no siloed discipline. **Key Responsibilities:** * Architect and implement RAG pipelines using MongoDB, Qdrant, and PostgreSQL. * Design deterministic, debuggable agent workflows with LlamaIndex/LangChain. * Build front‑end UI with React, TypeScript, and Tailwind CSS, emphasizing state management and performance. * Develop back‑end services with FastAPI/Django, async APIs, and event‑driven patterns. * Set up and maintain cloud infrastructure (AWS/Azure), Docker containers, Terraform scripts, and CI/CD pipelines. * Optimize latency, cost, and re‑ranking logic for production workloads. * Prototype rapidly and transition prototypes to production‑ready systems. **Required Skills:** * Deep proficiency in Python and TypeScript. * Experience with React, FastAPI/Django, and async patterns. * Strong understanding of MongoDB, Qdrant, and PostgreSQL. * Hands‑on with agent orchestration (LangChain/LlamaIndex), vector search, and structured outputs. * Familiarity with Docker, Terraform, CI/CD, and cloud services (AWS/Azure). * Proven track record building production RAG or agentic workflows. * Self‑directed, “default‑to‑ship” mindset; thrives without project‑manager oversight. **Required Education & Certifications:** * Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience). * Relevant certifications (e.g., cloud, data engineering) are a plus but not mandatory.

Vancouver, Canada

Hybrid

04-02-2026