Senior DevOps Engineer - AI & Data Infrastructure

Goodnotes

Our Values:

Dream big - Be visionary, strategic, and open to innovation Build great things - Work in service of our users, always improving and pushing higher Operate like an owner - Take responsibility with bold decision-making and bias for action Win like a sports team - Be trusting and collaborative while empowering others Learn and grow fast - Never stop learning and iterate fast Share our passion - Share ideas and practice enthusiasm and joy Be user obsessed - Empathetic, inquisitive, practical

About the team:

AI team in Goodnotes is looking to transform education and productivity using the latest technologies. We are working on helping students and teachers learn and teach more efficiently, and aim to achieve this by developing tools for Goodnotes AI and more foundational technologies like subject-oriented handwriting recognition. You will join a distributed team across Europe and Asia focusing specifically on building infrastructure for running our end-to-end AI technology. You will work alongside other engineers, as well as iOS engineers, machine learning engineers, QAs and designers to build and improve our new suite of AI features. Type of AI technologies running on our infrastructure include large language models, math solvers, handwriting recognition systems, etc. Besides models, our backend engineering team is building a holistic data engineering pipeline for training and production data.

About the role:

Do you believe in automating yourself out of a job? With our company's growth, that’s not going to happen anytime soon. Join a fast-growing and talented Platform Team to build a modern, strong and stable platform to accelerate the rollout of many new features, for millions of users around the world! This is the role for you, if you’re excited to work on the things listed below:

• Design,      build, and maintain the Goodnotes infrastructure, ensure it adheres to      Dickerson’s Hierarchy of Reliability.

• Build      CI/CD pipelines for AI and Data Infrastructure workloads

• Define      IaC surrounding our lakehouse infrastructure on AWS.

• Be      the go-to person for higher-level escalation for applications

• Improve      the system monitoring, health reporting, and logging

• Design      and implement security, assist in maintaining information security      practices and procedures

The tech stack

• Monitoring      and Logging: We are currently using Datadog for monitoring, APM, logging,      CI/CD optimization, Budget and cost management. Metrics are collected      across our agents, taken from the logs using metric filters, and updated      directly from lambda function or the application.

• Infrastructure-as-Code:      most of our infrastructure is written and defined in Terraform using      Atlantis

• CI/CD:      We are currently using GitHub Actions for our backend applications and      CircleCI for our iOS applications.

• Deployments:      We have multiple EKS clusters set up either for Blue/Green rollouts or      dedicated feature sets. We manage the workload configurations using ArgoCD      and Helm.

• Lakehouse:      Mainly on AWS infrastructure, including Athena, S3 Table, DBT, Kafka, and      SQS

• AI      infrastructure with external AI providers, large-scale backend bonus Ray      on EKS

The skills you will need to be successful in the above:

• Familiarity      with lakehouse architecture or large-scale AI systems

• Some      background in back-end development, including API usage and creation.

• Deep      understanding of Linux and Networking fundamentals.

• Strong      knowledge of network and container security.

• Extensive      experience working with AWS products.

• Proficiency      in container orchestration, with a particular emphasis on Kubernetes.

• Familiarity      with distributed databases.

• Proven      track record in building and maintaining CI/CD pipelines.

• Proven      experience in managing Relational and Non-relational databases, including      backup and restore operations.

• Proficiency      in automation/configuration management tools like Terraform.

• Proficiency      in scripting languages, particularly Python.

• Even      if you don’t meet all the criteria listed above, we would still love to      hear from you! Goodnotes places a lot of value on learning and development      and will support your growth if needed.

• Bonus:      If you are familiar with running workloads inside China

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Even if you don’t meet all the criteria listed above, we would still love to hear from you! Goodnotes places a lot of value on learning and development and will support your growth if needed. The interview process:

• Introductory      call with someone from our talent acquisition team. They want to hear more      about your background, what you are looking for, and why you’d like to      join Goodnotes

• Take-home      challenge to set up an end-to-end CI/CD pipeline for an API.

• Live      coding call with one of our engineers. This is where you get to see what      it would be like working at Goodnotes as well as the chance to ask any      engineering questions you may have

• Behavioural      interview with your manager: This is the person who will be managing you      day to day, working on your growth and development with you as well as      support you throughout your career at Goodnotes

• Panel      interview asking behavioural questions on our company values

What’s in it for you:

• Meaningful      equity in a profitable tech startup

• Budget      for things like noise-cancelling headphones, setting up your home office,      personal development, professional training, and health & wellness

• Sponsored      visits to our Hong Kong or London office every 2 years

• Company-wide      annual offsite (we met in Portugal in 2023 and Bali in 2024, Turkiye and      Korea in 2025)

• Flexible      working hours and location

• Medical      insurance for you and your dependents