Senior AI Engineer

YOU TASKS AND RESPONSIBILITES

• Design and develop backend services using Python, integrating multiple LLM providers via LiteLLM routing
• Build and maintain the frontend application using TypeScript, React 19, and Next.js 16 with Mantine UI components and Tailwind CSS
• Implement and extend LLM agent orchestration using LangChain/LangGraph, including stateful agent workflows, tool calling, and middleware pipelines
• Develop and maintain MCP server/client integrations for extensible tool ecosystems
• Design and optimize database schemas and queries across PostgreSQL, Redis, and Qdrant
• Manage cloud infrastructure on Alibaba Cloud
• Build and maintain CI/CD pipelines using GitHub Actions, including Docker image builds, automated testing, and multi-environment deployments
• Manage Kubernetes workloads including Helm charts, autoscaling, CronJobs, and sandboxing
• Implement and maintain observability stack: Langfuse, Prometheus, Grafana dashboards, and error tracking
• Integrate AI capabilities into production workflows: RAG pipelines, document parsing, voice agents, code sandboxing, and research tools
• Implement background job processing with Redis Queue and design scalable async architectures
• Ensure production reliability through proper monitoring, alerting, and incident response
• Maintain comprehensive API documentation and follow API versioning best practices
• Communicate effectively in English (spoken and written) with international cross-functional teams on a daily basis
• Participate in code reviews, architectural discussions, and technical decision-making
• Document architectural decisions and maintain knowledge-sharing resources

WHO YOU ARE

• Excellent English oral and written communication skills — daily collaboration with international teams requires fluent spoken English
• Strong Python development experience — FastAPI, async programming, SQLAlchemy/SQLModel, Pydantic, and production-grade API development
• Experience with LLM application development — LangChain, LangGraph, or similar LLM orchestration frameworks; prompt engineering; RAG pipelines; multi-provider LLM integration
• Frontend development with TypeScript and React — Next.js, state management, component libraries, and Tailwind CSS
• Infrastructure as Code experience — Terraform, managing cloud resources declaratively
• Kubernetes and container orchestration — deploying and managing workloads on managed Kubernetes, Helm charts, autoscaling
• Cloud platform experience — Alibaba Cloud or AWS; services including managed databases, object storage, container registries, load balancers, and secrets management
• Database proficiency — PostgreSQL, Redis, and vector databases