SRE - DataOps/MLOps

Autify, Inc. is a startup founded in San Francisco. As the first Japanese team to graduate from the Alchemist Accelerator, we have taken on the global market with our mission to “enhance people’s creativity through the power of technology.”

Since our launch in 2019, we have been systematically reducing QA’s dependence on manual work. Autify Genesis standardizes QA operations by using AI to handle documentation tasks such as test design, planning, and reporting. Autify Aximo enables AI to autonomously interpret and interact with user interfaces—without the need for scripting. Autify Nexus continuously runs scripted regression tests at low cost, with speed and stability. By putting AI at the center of every stage—thinking, executing, and repeating—we are building a world where QA can operate without relying on manual intervention.

Today, these products have come together as the Autify Platform, providing comprehensive support across the entire QA process, from test design through execution. Autify AI Coworker combines these products with professional QA services to take ownership of the entire process, from test design to execution. Rather than simply providing tools, we transform the work itself—and this approach is already delivering results that existing solutions have been unable to achieve.

We are transforming testing through people and technology, turning quality into a competitive advantage for businesses. And this transformation is only just beginning.

We are now looking for people who want to help make that transformation a reality. Your work will help redefine the standard for development teams around the world.

You will oversee Autify’s backend development and build the infrastructure, the AI-based software test automation platform and the data pipeline. In order of importance, this person will support infrastructure and platform development, data engineering, and machine learning. 

| About the engineering team
Our team
Our engineering team is composed of 14 members, of developers, QA engineers, leadership, SRE.We are all from different backgrounds and work efficiently in a multi-cultural environment.The team is fully agile, and AI enabled, with all teams building their own agentic flows, both in product and in the pipeline. 
Our development process
Given the nimble nature of small teams and speed of development required in 2026 the teams are focusing on fine tuned processes, and tooling, adapted to their own needs.
Many traditional roles and responsibilities remain, with our product team prioritizing and defining the roadmap with our stakeholders, QA engineers designing the testing scope and framework through our own products.For the SRE team in particular, the process is project oriented, with a kanban based ticketing approach for operational requests, and a more focused time for long tailed deliveries. 
Tech culture/support
Tech is selected at each staff's discretion, little to no red tape
Innovation is encouraged, budget per person enable a lot of flexibility in trying technologies
We actively work on technical debt
There is technical skill improvement support (learning support allowance)
PC with the staff's desired specs, external monitors, etc. can be rented from the company

Tech stack

Backend: Node, Go, Ruby, Ruby on Rails

Frontend: JavaScript, TypeScript, React, Redux, Styled Components

Machine learning: Python

Database: PostgreSQL, Redis

Test: Autify Nocode, Autify Nexus, Autify Aximo

Infrastructure: AWS, Docker, GCP, Terraform, Packer

Monitoring: Sentry, Datadog, Drata

CI/CD: CircleCI, GitHub Actions

Source code management: GitHub

Project management: Internal

Misc.: G Suite, Slack, Notion, Discord, 1Password, etc.

| Employment Conditions

Employment Status

Permanent employee (Full-time)
Probation period: 6 months after joining the company (conditions are the same as permanent employment)

Work Location

Remote in Japan or Tokyo office (6F, Cross C Higashi-Nihonbashi Building, 2-22-1 Higashi-Nihonbashi, Chuo-ku, Tokyo)
This is a hybrid work arrangement that requires employees to work from the office three days a week.

Work Hours

Full flextime time
Note: The determination of working hours (start and end times) must be made to the extent that one's own duties (including guidance and supervision of subordinates) are properly performed and that there are no obstacles to work in terms of coordination and communication with other employees.

Holidays/PTO

Complete a five-day workweek system (National holidays, Year-end and New Year holidays, etc.)
Unlimited paid time off 

Benefits

Equipped with various social insurance
Regular health checkups
Stock option
A laptop PC will be rented when joining the company

| Responsibilities
• Infrastructure development using AWS and GCP
• Manage containers, Terraform, etc
• Build and operate clean, reliable data pipelines
• Keep our systems up and running to meet our SLO
• Develop and maintain AI-powered systems to improve and operate our systems
• Develop and maintain the MLOps platform and CI/CD pipelines for training, deploying, and serving machine learning models.
• Collaborate with the peer teams to operationalize and scale machine learning systems.
• Support the engineering teams in research, innovation, optimization and validation of different capabilities for our ML based offering

| Required QualificationsRequirements
One of:
Japanese nationals
Foreign nationals qualified to work in Japan
Foreign nationals who are not working in Japan and require a visa and meet any of the following conditions:
Bachelor's equivalent in engineering, science and engineering, informatics, etc
Ten years of work experience
 
※  Candidates currently based in Japan will be prioritized.
※  If you currently live overseas, you may work as a subcontractor until you obtain a visa. Required skills
Over 3 years of experience in developing, deploying, and operating highly reliable backend systems and infrastructure
Over 1 year of experience in building infrastructure using container management services such as Docker, Kubernetes, and AWS Elastic Container Service
Over 1 year of experience in data engineering, specifically including:
Developing and maintaining data pipelines
Managing data governance aspects such as data classification, retention, and secure data access, particularly in development and test environments
Experience in technology selection and and system architecture design
Experience in improving SLA/SLO
English skills (Business level or better)

| Nice-to-Have
Experience with data pipelines and database management
Experience with MLOps:
developing and maintaining ML CI/CD pipelines for model lifecycle
implementing observability for production ML model performance and data quality
Modern development experience with Agile methodologies.
Experience in an on-call rotation

| Desired Personality Traits
Takes ownership and stays involved until the end
Produces results in the shortest time without overly seeking perfection
Has high and clear ideals and self-awareness and spares no effort for self-growth
Faces issues from the user's point of view and sympathizes
Has a high awareness of reliability, security, and performance
Prefers to to automate operations

| Selection Process