Founding Infra
2 days ago
About the role
You'll own the foundation of Known's product infrastructure across mobile, web, and agentic AI systems. From data pipelines to cloud infra, you'll design, build, and scale the platform that powers matching, voice, and scheduling features.
Responsibilities- Design and manage AWS-based infrastructure, codified in Terraform.
- Build and maintain data ingestion/orchestration pipelines (Airflow, Dagster, or equivalent).
- Administer and optimize PostgreSQL (with pgvector) and data warehouse environments.
- Support data modeling and schema design for user profiles, matching, and conversation logs.
- Collaborate with AI/ML engineers to productionize models (training, inference, monitoring).
- Implement observability (logging, metrics, alerts) across the stack.
- 4+ years in platform, infra, or data engineering.
- Proficiency in Python, Bash, YAML; experience with containerization (Docker, Kubernetes).
- Strong knowledge of cloud architecture, data pipelines, and infra-as-code.
- Exposure to ML/AI workflows and feature stores a plus.
- Strong data eng/pipeline background so that they can work closely with MLE on data related projects too.
- Typescript expert that is also familiar with postgres/cloud infra
- Stand up a data lake + warehouse for storing structured behavioral signals.
- Build ingestion from app + third-party APIs (e.g. Stripe, OpenAI, Twilio).
- Scale infra for real-time voice agent calls and user profile matching.
We're seeking a Founding Infrastructure & Platform Engineer with 4+ years of experience in platform, infrastructure, or data engineering. You should be comfortable designing and managing AWS-based infrastructure, building data ingestion pipelines, and optimizing PostgreSQL environments. A strong data engineering/pipeline background is crucial, and expertise in Typescript is a significant plus. You'll be instrumental in building the core infrastructure that powers Known's AI-voice led matchmaking platform.
What you'll do:
- Design and manage AWS-based infrastructure, codified in Terraform.
- Build and maintain data ingestion/orchestration pipelines (Airflow, Dagster, or equivalent).
- Administer and optimize PostgreSQL (with pgvector) and data warehouse environments.
- Support data modeling and schema design for user profiles, matching, and conversation logs.
- Collaborate with AI/ML engineers to productionize models (training, inference, monitoring).
- Implement observability (logging, metrics, alerts) across the stack.
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