2 месяца назад
Software Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer (AI/Experimentation Systems): Building and scaling distributed systems for experimentation platforms, feature flags, and cost-effective data analytics with an accent on scalable architecture, resource allocation, and AI-native workflows. Focus on designing agentic workflows, operating Kubernetes-based services, optimizing cloud resource usage, and safely rolling out or rolling back product changes.
Location: Hybrid, Minato City, Tokyo, Japan; office in Roppongi
Company
operates a marketplace platform focused on circulating value and connecting people through technology.
What you will do
- Design and maintain scalable distributed systems for experimentation, feature flags, access control, resource allocation, and cost optimization.
- Implement and maintain features in an existing codebase and scale the current product to handle 10x load.
- Build systems supporting AI-native workflows, including automated configuration, control, and data utilization through AI agents.
- Operate and debug services using observability metrics and Kubernetes.
- Define, test, deploy, and independently deliver core features while collaborating with technical and non-technical stakeholders.
Requirements
- Professional experience with Go, Python, and TypeScript.
- Good computer science fundamentals and experience with cloud technologies.
- Understanding of scalable distributed systems, stateless API design, and protocols such as gRPC.
- Ability to develop a foundation in Domain-Driven Design, Event Sourcing, and Service-Oriented Architecture.
- English proficiency at B2 level or above.
- Japanese at A2 level is optional.
Nice to have
- Experience with Bazel, Cuelang, Terraform, GCP, or Kubernetes.
- Experience implementing parsers and virtual machines.
- Knowledge of memory allocation optimization.
Culture & Benefits
- Full flextime work with no core hours.
- Engineering principles include product passion, continuous growth, mechanism-based problem solving, and open collaboration.
- Work on an experimentation platform that enables scalable A/B testing and safe feature rollouts and rollbacks.
Hiring process
- Application screening followed by a technical skill assessment through HackerRank or GitHub.
- Interviews, reference checks, and a final offer decision based on the interview and references.
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