锦鲤求职岗位描述
The Role：
Join the IT Application Business Intelligence team at Tesla Shanghai Gigafactory to build the next generation of enterprise data products: production LLM agents for conversational, tool-augmented analytics on complex, large-scale, governed data—not dashboards alone.
Enterprise warehouses and analytics platforms must evolve for agent-driven workloads: new access patterns, APIs, and performance engineering for tool calls, multi-turn dialogue, and high concurrency. You will own both agent systems and this platform shift, in partnership with data engineers, with clear boundaries and reusable capabilities.
Responsibilities：
Design, build, deploy, and operate LLM agents for factory and enterprise analytics, including tool calling, workflows, evaluation, and production monitoring.
Develop backend services that connect agents to data warehouses, semantic/metrics layers, and big-data platforms (governed SQL, data APIs, and standard enterprise access patterns).
Deliver interactive, multi-turn analysis with business users: intent clarification, large-scale structured data, and explainable results.
Own agent infrastructure: knowledge bases, search and vector indexes as required, conversation state, authorization, and audit trails.
Evolve warehouse and serving architecture for agent interaction—access layers, APIs, and governance—and optimize for latency, throughput, cost, and reliability.
Integrate agents with internal products across manufacturing, supply chain, and regulatory/compliance data services. Uphold production standards: CI/CD, observability, and on-call.
Requirements：
3+ years of software engineering with production systems shipped and operated.
Proven experience building and deploying LLM agents (tool use, orchestration, deployment, and iteration—not prototypes only).
Strong analytics engineering: complex SQL, large datasets, metrics, and data quality.
Hands-on development or operations on data warehouse / big-data platforms (e.g. Hive, Spark, Airflow, distributed SQL engines, ClickHouse or comparable OLAP), including platform work driven by analytical or agent workloads.
Backend proficiency in Python and/or Java (REST APIs, databases, distributed systems fundamentals).
Effective communication in English and Mandarin with factory and IT stakeholders.
Strong problem-solving, ownership, and collaboration.
Preferred Qualifications
Domain experience in manufacturing, supply chain, or regulatory/compliance data services.
Building and operating large-scale data platforms (ingestion, scheduling, serving, reliability).
Background in electric vehicles, robotics, or industrial manufacturing.
Experience with enterprise data platforms in global manufacturing, automotive, or technology organizations.
Demonstrated architecture or performance improvements on warehouses or analytics platforms to support LLM agents, conversational analytics, or high-interaction query patterns.