Yuno - Senior Platform Engineer — AI Agent Infrastructure

• Event-driven architecture and messaging systems — you've designed systems around message queues (Kafka, NATS, RabbitMQ, or similar). You understand at-least-once delivery, consumer groups, dead letters, backpressure, and ideally have migrated a system from synchronous to async messaging. • AWS — deep experience with EC2, VPC, IAM, S3, RDS. You understand networking because inter-service communication runs over internal VPC. • Databases — solid knowledge of both SQL (PostgreSQL) and NoSQL (MongoDB, Redis). You understand when to use each, indexing strategies, replication, and performance tuning. • Docker — container lifecycle, resource limits, health checks, bind mounts, multi-stage builds. • Distributed systems debugging — you've debugged async flows and cascading failures across services in production, and can explain what failed and how you fixed it. • Infrastructure as Code — Terraform or Pulumi. You believe infrastructure should be reviewed in PRs, not clicked in consoles. • Observability — Datadog fluency or equivalent (dashboards, monitors, APM, log pipelines, distributed tracing). • Tech Stack — hands-on experience with Go, AWS (EC2, S3, VPC, RDS PostgreSQL), Docker, PostgreSQL, MongoDB, Redis, and Datadog. • AI / MLOps infrastructure — experience running AI workloads in production (model serving, LLM inference, GPU/resource management, agent evaluation and observability tools like LangFuse, LangSmith, Braintrust, MLflow). • Multi-tenant container platforms — experience with platforms that run customer/user workloads in containers (Replit, Railway, Fly.io, or internal PaaS systems). • Kubernetes — you've done the migration from "Docker on bare EC2" to K8s at least once and know what breaks during the transition. • Data pipelines and orchestration — Airflow, Prefect, or similar. Knowledge of data warehouses (Databricks, Snowflake, BigQuery) is a plus • s6-overlay for container process supervision. • Experience with AI agent framework ecosystems.