SRE - DataOps/MLOps

The Global QA Market As software development continues to accelerate at an unprecedented pace, QA remains stuck in an outdated, labor-intensive model. Test engineers are chronically in short supply, outsourcing costs continue to rise, and even with the introduction of SaaS tools, day-to-day operations remain a bottleneck. This dilemma is not a tooling problem—it is a structural problem with QA itself.Now, for the first time, the conditions are in place to change that structure. With AI capable of making decisions, taking action, and correcting itself autonomously, we have a unique opportunity to fundamentally transform QA and break its long-standing dependence on human labor. We intend to seize that opportunity. About Autify 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. About This Role Job Purpose 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.  Work with other engineers, designers, and product leads to implement various features while considering performance, security, and reliability. Proactively identify functions that can be improved from the reliability perspective. Facilitate future development by improving the system on the existing server and infrastructure, code quality, monitoring, CI/CD pipeline, etc. About the engineering team Our team Our engineering team is composed of 14 members, of developers, QA engineers, leadership, and SREs.We are all from different backgrounds and work efficiently in a multicultural 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 the 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 member's discretion, with little to no red tape Innovation is encouraged; budget per person enables 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 Testing: Autify NoCode, Autify Nexus, Autify Aximo Infrastructure: AWS, Docker, GCP, Terraform, Packer Monitoring: Sentry, Datadog, DrataCI/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 SLOs 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 Qualifications Requirements 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 system architecture design Experience in improving SLA/SLOEnglish 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 automate operations Selection Process Technical Interview with hiring manager Cultural fit interview Interview with VP of Engineering Reference check