about the company.
AI for Science.
about the team.
IT Operation.
about the job.
1. Own the architecture and day-to-day management of our multi-cloud environment across AWS, Azure, and other cloud providers — covering networking, security, cost, and workload placement.
...
2. Design and build AI Agent solutions end-to-end, from use-case scoping through production deployment and evaluation.
3. Partner with internal teams to drive AI transformation — identify high-value use cases, prototype Agent workflows, and hand off with documentation and training.
4. Set cloud and AI engineering standards (CI/CD, IaC, observability, security) and drive adoption across teams.
5. Advise leadership on cloud strategy, AI roadmaps, and build-vs-buy decisions; provide architectural guidance and post-incident review for major production issues.
skills and experience required.
1. 7+ years in software engineering or solution architecture, with demonstrated leadership in multi-cloud architecture and hands-on AI Agent development. Strong Python skills required.
2. Hands-on production experience on at least two major cloud platforms (e.g., AWS, Azure, GCP or leading China domestic clouds such as Alibaba Cloud, Tencent Cloud) — networking, IAM, cost, and security.
3. Proven track record shipping AI Agent applications — LLM APIs, agent frameworks (e.g., LangChain, LangGraph, MCP, or similar), RAG pipelines, and evaluation.
4. Solid grounding in Kubernetes, Docker, Terraform (or equivalent IaC), and CI/CD.
5. Experience driving internal AI adoption — scoping use cases, running POCs, and coaching teams through change.
6. Strong communicator in English and Mandarin, comfortable with both technical and business audiences.
show more
about the company.
AI for Science.
about the team.
IT Operation.
about the job.
1. Own the architecture and day-to-day management of our multi-cloud environment across AWS, Azure, and other cloud providers — covering networking, security, cost, and workload placement.
2. Design and build AI Agent solutions end-to-end, from use-case scoping through production deployment and evaluation.
3. Partner with internal teams to drive AI transformation — identify high-value use cases, prototype Agent workflows, and hand off with documentation and training.
4. Set cloud and AI engineering standards (CI/CD, IaC, observability, security) and drive adoption across teams.
5. Advise leadership on cloud strategy, AI roadmaps, and build-vs-buy decisions; provide architectural guidance and post-incident review for major production issues.
skills and experience required.
1. 7+ years in software engineering or solution architecture, with demonstrated leadership in multi-cloud architecture and hands-on AI Agent development. Strong Python skills required.
...
2. Hands-on production experience on at least two major cloud platforms (e.g., AWS, Azure, GCP or leading China domestic clouds such as Alibaba Cloud, Tencent Cloud) — networking, IAM, cost, and security.
3. Proven track record shipping AI Agent applications — LLM APIs, agent frameworks (e.g., LangChain, LangGraph, MCP, or similar), RAG pipelines, and evaluation.
4. Solid grounding in Kubernetes, Docker, Terraform (or equivalent IaC), and CI/CD.
5. Experience driving internal AI adoption — scoping use cases, running POCs, and coaching teams through change.
6. Strong communicator in English and Mandarin, comfortable with both technical and business audiences.
show more