AI Platform Engineer – MLOps/LLMOps

Woven Planet

. Design, implement, and operate MLOps/LLMOps platforms and shared workflows .

Posted 10/19/2026full-timeTokyo • JapanJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating MLOps and LLMOps platforms, with a strong focus on automation, monitoring, and quality evaluation of AI systems. Proficient in software development using Python and experienced in CI/CD and Infrastructure as Code methodologies.

Highest-signal resume keywords

MLOps ExperienceLLMOps ExperienceCI/CD AutomationPython Software DevelopmentCloud Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

MLOpsLLMOpsPlatform EngineeringCI/CDInfrastructure as CodePythonModel ManagementQuality EvaluationAgent SystemsMonitoring Mechanisms

Soft Skills

CollaborationCommunication

Tools & Technologies

Container TechnologiesCloud PlatformsObservability Tools

Industry Keywords

AI Quality EvaluationModel TraceabilityExperiment ResultsSafety RisksFeedback Loops

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

Design, implement, and operate MLOps/LLMOps platforms and shared workflows
Build systems for management and traceability of models, prompts, agent configurations, evaluation data, experiment results, and release information
Partner with AI Quality Evaluation Engineers and product development teams on feedback loops, evaluation execution, regression evaluation, and release decisions
Build and operate mechanisms to visualize and monitor LLM output quality, safety, consistency, latency, cost, and usage
Establish testing, monitoring, alerting, and rollback mechanisms for detecting quality degradation and safety risks
Automate AI workload development and operations using CI/CD, Infrastructure as Code, container and cloud platforms, and observability tools such as logs, metrics, and traces
Design and implement safe, effective, and auditable agent systems for code generation, modification, and review
Work closely with product development teams, ML engineers, and security and cloud infrastructure stakeholders
Report to a functional leader
Travel to Woven City several times per month

Requirements

What you’ll need

2+ years of professional experience in MLOps, LLMOps, or Platform Engineering
Experience designing, implementing, and operating platforms supporting the development, evaluation, deployment, and operation of LLM systems
Experience automating development or operational processes using CI/CD, Infrastructure as Code, container technologies, and cloud services
Software development experience using Python
Business-level proficiency in English
Conversational-level proficiency in Japanese

Benefits

Comp & perks

Competitive salary based on experience
Flexible working time
Paid holiday: 20 days per year (prorated)
Sick leave: 6 days per year (prorated)
Saturdays, Sundays, Japanese National Holidays, and other company-defined holidays
Japanese Social Insurance: Health Insurance, Pension, Workers’ Compensation, Unemployment Insurance, and Long-term Care Insurance
Housing allowance
Retirement benefits
Rental cars support
In-house training program, including software study and language study
Equal opportunity employer valuing diversity