Genie Platforms
AI SDR / GTM platform
Senior Software Engineer · AI Platform
Server-side platform for conversational AI used by sales, RevOps, and go-to-market teams — an AI SDR that has to run as production services, not a chat demo.
01What I built
Owned server-side technical direction and roadmap for the Genie Platforms backend. Designed the NestJS microservice layout, APIs, and Kafka paths, and wired persistence across PostgreSQL, MongoDB, and Redis plus partner integrations. The GTM clients are the product surface; this engagement was the services underneath them.
- Server-side microservice architecture and API contracts
- Kafka streaming paths between services
- Persistence across PostgreSQL, MongoDB, and Redis
- Partner and third-party integrations on the AWS / Kubernetes path
02Engineering proof
- NestJS microservice backend on Kubernetes / AWS
- Kafka between services instead of one process talking to every store
- PostgreSQL, MongoDB, and Redis as separate persistence concerns
04Problem
Conversational GTM workflows had to run as evented production services: APIs, partner integrations, and several data stores — not a standalone prototype that dies when a third-party call fails.
05Scale & constraints
- Event-driven microservice backend
- Polyglot persistence: PostgreSQL, MongoDB, Redis
- Third-party and partner API integrations
- Kubernetes on AWS as the runtime
06Outcome
A production microservice backend on Kubernetes / AWS, with Kafka-backed integrations instead of a single service talking to every store. Throughput and conversion figures are not published.
- Microservice backend in production on Kubernetes / AWS
- Kafka paths across PostgreSQL, MongoDB, and Redis
07Stack
- Node.js
- NestJS
- KafkaJS
- PostgreSQL
- MongoDB
- Redis
- Kafka
- Docker
- Kubernetes
- AWS
- Amplication
No verified public metrics are published for this engagement.
Categories: AI, SaaS
Year: 2024