Why this role stands out
This role offers an exciting opportunity to shape the future of intelligent mobility by building the AI engineering platform for a leading smart technology company, with hybrid flexibility to support your work-life balance. If you are a seasoned software engineer passionate about distributed systems and automation, you'll thrive by driving innovation and collaborating with diverse teams to create impactful solutions. Apply today to join XPENG's forward-thinking environment and contribute to cutting-edge advancements in AI and autonomous driving.
Quick overview
Job description
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Design, build, and operate production-grade platform services and infrastructure with strong reliability, observability, and performance.
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Identify manual, repetitive engineering workflows and eliminate them through self-service automation on the platform.
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Build and evolve the agentic layer: agent lifecycle, tool/MCP integrations, sandboxed execution, multi-agent workflows.
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Design the semantic data layer that grounds agents: model our systems, workflows, and decision data as connected objects and tools that agents can query and act on.
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Build safe action execution paths: connectors to internal and operational systems, staged propose–validate–approve–commit flows, with granular access control and end-to-end decision lineage/audit.
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Own system design for new platform capabilities end to end, from requirements through rollout and operations.
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Work directly with customers: lead technical onboarding, gather requirements, debug production issues, and turn field feedback into roadmap priorities.
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Establish best practices for agent evaluation, observability, and safety guardrails.
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Master's degree in Computer Science, Software Engineering, or related fields.
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5+ years building and operating production distributed systems, with demonstrated strength in system design and software engineering fundamentals.
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Proficiency in Python and TypeScript; solid grasp of databases, message queues, caching, and API design.
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A builder's instinct for automation: a track record of turning manual processes into tools, pipelines, or self-service systems.
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Hands-on experience with modern AI coding tooling and LLM APIs, including tool use/function calling.
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Experience with agentic systems or task orchestration platforms (workflow engines, multi-agent frameworks, MCP servers, or similar).
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Strong cross-team communication skills.
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Familiarity with Autonomous Driving terminologies and model development workflows.
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Direct customer-facing experience: solutions engineering, technical onboarding, developer relations, or enterprise support.
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Experience with data/domain modeling: semantic layers, knowledge graphs, or object models over heterogeneous data sources.
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Experience integrating with enterprise or operational systems (internal platforms, legacy APIs, writeback to systems of record).
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Experience with evaluation frameworks and observability for LLM applications.
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Familiarity with sandboxing/isolation technologies.
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Contributions to open-source agent frameworks, MCP servers, or developer tools.
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Experience driving adoption of developer tooling within engineering organizations.
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A fun, supportive and engaging environment.
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Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving.
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Opportunity to work on cutting edge technologies with the top talent in the field.
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Competitive compensation package.
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Snacks, lunches and fun activities.
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