Infra / Platform Engineer - Known
Remote • San Francisco • FullTime
Posted 1y ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Known is seeking a foundational engineer to own its core infrastructure and platform systems, which power AI-driven matching, voice, and scheduling experiences. This role involves designing and scaling cloud infrastructure, data orchestration, performance monitoring, and model deployment assistance to ensure the platform is fast, reliable, and secure. You will collaborate directly with the founding team, including AI/ML, product, and design, to establish the company's technical foundation, influencing architecture, engineering culture, and best practices from the outset. This position is ideal for a pragmatic builder who thrives in early-stage environments, enjoys building from scratch, and prioritizes reliability, velocity, and simplicity.
Responsibilities
- Design and manage cloud infrastructure, primarily AWS, using Infrastructure-as-Code (Terraform).
- Establish CI/CD pipelines and best practices for rapid and safe iteration using tools like GitHub Actions, Docker, and Kubernetes.
- Build and maintain scalable data ingestion and orchestration pipelines for ML and product analytics.
- Administer and optimize PostgreSQL databases (including pgvector for embeddings) and analytical warehouses.
- Collaborate with AI/ML engineers on deploying and monitoring LLM and matching models for inference, evaluation, and retraining.
- Implement observability (logging, metrics, traces, alerts) across backend services, data jobs, and model endpoints.
- Drive reliability and scalability for web, mobile, and agentic systems, including real-time voice matching and batch workflows.
- Collaborate cross-functionally with product, design, and ML teams to align infrastructure with user and business needs.
Requirements
- 4+ years of experience in infrastructure, platform, or data engineering, preferably in startup or high-growth environments.
- Strong proficiency in Python, TypeScript, and scripting languages like Bash and YAML.
- Deep understanding of cloud architecture (AWS, GCP, or similar) and Infrastructure-as-Code (Terraform, Pulumi, or CloudFormation).
- Solid experience with containerization and orchestration technologies (Docker, Kubernetes, ECS).
- Proven ability to design and operate data pipelines and distributed systems.
- Experience with PostgreSQL, data modeling, and schema design for real-time and analytical workloads; pgvector or embeddings experience is a plus.
- Familiarity with ML/AI workflows (model training, inference, monitoring) and feature stores is beneficial.
- Solid understanding of DevOps fundamentals, including observability, cost optimization, and security.
- Possess a collaborative mindset, strong ownership, and a bias for shipping working systems quickly.