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Senior Platform Engineer — AI Agent Infrastructure

4 weeks ago
Spain, Mexico, Argentina, Brazil, Chile, Colombia, Europe, Belgium, Paraguay, Peru, Germany, Italy, Netherlands
Full-time
Senior
AI Engineer
DevOps and Infrastructure
Apache Airflow AWS Databricks Datadog Docker EC2 GCP Go Kafka Kubernetes MLflow MongoDB NATS PostgreSQL Prefect Pulumi RabbitMQ Redis Snowflake Terraform
Apply Now

Yuno

Yuno is a payment orchestration and financial infrastructure platform for global businesses. It centralizes payment methods, PSPs, fraud tools, routing, reconciliation, checkout, payouts, and other payment workflows through a single API.

Payment Processing Software
51-200
Founded 2022
View All Jobs 24

Description

  • Own the cloud infrastructure for the AI agent platform and automate provisioning with infrastructure as code.
  • Design and implement event-driven messaging for reliable asynchronous inter-service communication.
  • Improve streaming reliability and reduce dependence on synchronous service interactions.
  • Build and maintain observability, including monitoring, tracing, alerting, and log pipelines.
  • Drive architectural decisions as the platform matures and grows.
  • Evaluate when and how to evolve the infrastructure and platform architecture.
  • Support reliability and incident response by making issues diagnosable through dashboards and alerts.
  • Collaborate on technology choices and system design for platform evolution.

Requirements

  • 4+ years of experience in platform, infrastructure, or related engineering roles.
  • Experience designing event-driven systems with message queues such as Kafka, NATS, RabbitMQ, or similar.
  • Strong AWS experience with EC2, VPC, IAM, S3, and RDS.
  • Solid knowledge of PostgreSQL and NoSQL databases such as MongoDB and Redis, including indexing, replication, and performance tuning.
  • Hands-on Docker experience, including container lifecycle, resource limits, health checks, bind mounts, and multi-stage builds.
  • Experience debugging distributed systems, async flows, and cascading failures in production.
  • Experience with infrastructure as code tools such as Terraform or Pulumi.
  • Fluency with observability tools such as Datadog or equivalent, including dashboards, monitors, APM, log pipelines, and distributed tracing.
  • Hands-on experience with Go and the listed tech stack: AWS, PostgreSQL, MongoDB, Redis, Docker, and Datadog.
  • Preferred experience running AI or MLOps workloads in production, including model serving, LLM inference, GPU/resource management, or agent evaluation tools like LangFuse, LangSmith, Braintrust, or MLflow.
  • Preferred experience with multi-tenant container platforms such as Replit, Railway, Fly.io, or internal PaaS systems.
  • Preferred Kubernetes migration experience from bare-metal or single-host Docker setups.
  • Preferred experience with data pipelines/orchestration tools such as Airflow or Prefect, and familiarity with warehouses like Databricks, Snowflake, or BigQuery.
  • Nice to have: ECS experience, s6-overlay experience, and experience with AI agent framework ecosystems.

Benefits

  • Competitive compensation.
  • Remote work from anywhere.
  • Home office bonus to set up your workspace.
  • Work equipment provided.
  • Stock options.
  • Health plan available wherever you are.
  • Flexible days off.
  • Language, professional, and personal growth courses.

Interested in this position?

Apply directly on the company website

Apply Now

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