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Senior Platform Engineer — AI Agent Infrastructure

3 hours, 10 minutes ago
Spain, Europe, Belgium, Italy, Netherlands, Mexico, Argentina, Brazil, Chile, Colombia, Paraguay, Peru, Germany
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
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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 20

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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