Full-Time

DevOps Engineer

Mid-to-Senior Level

ONE

ONE

51-200 employees

AI-powered platform enabling on-demand fashion production

No salary listed

New York, NY, USA

Remote

Periodic travel to NYC or Dominican Republic hubs for team gatherings is optional.

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
Grafana
Github Actions
Grafana Logstash
Apache Kafka
Kinesis
Docker
CloudFormation
AWS
Elasticsearch
Prometheus
Jenkins
Terraform
DevOps
CircleCI
Kibana
Looker
Snowflake
Requirements
  • 5 or more years of experience in DevOps, Site Reliability Engineering, or related infrastructure engineering roles.
  • Track record of managing complex, distributed systems at scale.
  • Strong expertise in Amazon Web Services and cloud architecture including compute, storage, networking, and security.
  • Experience designing and maintaining scalable infrastructure using services like Elastic Compute Cloud, Elastic Container Service, Elastic Kubernetes Service, Simple Storage Service, Relational Database Service, Virtual Private Cloud, and Lambda.
  • Hands-on experience with containerization and orchestration, including managing production Kubernetes clusters and Docker.
  • Proven ability to create and manage Continuous Integration and Continuous Delivery pipelines using tools such as Jenkins, CircleCI, GitHub Actions, or Argo.
  • Experience implementing GitOps or similar practices to streamline deployments.
  • Proficiency in scripting and infrastructure-as-code using Terraform, CloudFormation, or equivalent tools.
  • Solid knowledge of monitoring and logging frameworks such as Prometheus, Grafana, Elasticsearch Logstash Kibana stack, and CloudWatch.
  • Familiarity with event-driven architecture and data pipelines, including messaging or streaming systems like Kafka or Kinesis.
  • Understanding of security best practices in cloud and DevOps, including managing secrets, Identity and Access Management roles, and Virtual Private Cloud security.
Responsibilities
  • Build, maintain, and scale Amazon Web Services cloud infrastructure using infrastructure-as-code and modern Continuous Integration and Continuous Delivery pipelines.
  • Manage Kubernetes clusters and containerized microservices, optimizing for high availability, security, and efficient resource usage.
  • Design and implement continuous integration and delivery pipelines for code and Machine Learning model updates.
  • Automate routine operations and workflows using scripts, Amazon Web Services Lambda functions, and other automation tools.
  • Implement monitoring, logging, and alerting to track system performance and reliability.
  • Troubleshoot and resolve infrastructure issues or bottlenecks across the stack to maintain high uptime.
  • Maintain and optimize event streaming and pipeline architecture using Kafka and its integration with Snowflake and Looker.
  • Collaborate with machine learning engineers to deploy and scale Artificial Intelligence and Machine Learning models in production.
  • Implement infrastructure for model training, inference, and performance monitoring in live environments.
  • Integrate and manage internal and third-party tools such as Hasura GraphQL engine and Airtable.
  • Champion DevOps best practices, including GitOps workflows and optimizing build and test pipelines.
Desired Qualifications
  • Experience working in a startup or building systems from scratch.
  • Exposure to Machine Learning Operations or Artificial Intelligence driven platforms, including experience deploying or managing machine learning models in production.
  • Familiarity with Machine Learning frameworks and services such as model serving or working with OpenAI Application Programming Interfaces.
  • Experience with data warehousing and analytics tools such as Snowflake or integrating Business Intelligence platforms like Looker into a data pipeline.
  • Familiarity with GraphQL Application Programming Interfaces and frameworks, specifically Hasura.
  • Experience with workflow orchestration tools like Argo Workflows, Airflow, or Tekton for running complex jobs and pipelines.
  • Experience managing serverless functions such as Amazon Web Services Lambda as part of a larger system.
  • Interest or experience in e-commerce, manufacturing processes, or fashion technology.

Resonance provides an AI-powered operating system for fashion called ONE that lets brands design, produce, and sell garments on demand with no excess inventory. ONE handles design to production on a single platform, enabling private labels and market-ready products in weeks, with on-demand manufacturing and easy sample creation. It differentiates itself by combining AI-driven design with end-to-end supply chain management for rapid, zero-waste production, serving established brands, emerging labels, and individual creators. Its goal is to make the fashion value chain more sustainable, efficient, and profitable by reducing waste and helping brands respond quickly to cultural trends.

Company Size

51-200

Company Stage

Seed

Total Funding

$48.8M

Headquarters

New York City, New York

Founded

2015

Simplify Jobs

Simplify's Take

What believers are saying

  • Manufacturing lab in Santiago enables fast delivery and low shipping emissions.
  • Free tier with 50+ materials drives e-commerce adoption; Pro at $100/month scales wholesale.
  • 'Design, sell, make' model eliminates 30% industry waste and inventory risk.

What critics are saying

  • Hurricanes disrupt Santiago lab, halting production in 12-24 months.
  • Amazon's AWS Fabric undercuts with scalable zero-inventory in 6-12 months.
  • Nike's Fabricate scales to 1M units daily, squeezing margins in 24-36 months.

What makes ONE unique

  • ONE is the first AI-powered operating system for on-demand fashion manufacturing at scale.
  • CreateOne simulates fabric drape, texture, and fit in 3D without physical samples.
  • Dynamic value chain routes orders across factories, optimizing for carbon and quality.

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