XPENG is looking for a Senior Staff AI Engineer to build and scale production-grade AI systems that drive measurable impact across internal teams, leveraging state-of-the-art LLM app stacks, retrieval-augmented generation, evaluation frameworks, and scalable serving. The role will define long-term architecture and engineering standards for Applied AI systems to maximize reuse, reliability, and impact across multiple product areas.
Requirements
- BS/MS/PhD in Computer Science or a related field, or equivalent experience.
- 10+ years of software engineering experience, with a proven track record delivering complex, production-grade systems.
- Deep technical expertise in AI/ML, with hands-on experience building and deploying systems using language models, retrieval/grounding (RAG), embeddings/vector search, and evaluation frameworks.
- Hands-on experience building and scaling agentic AI systems in production environments.
- Strong experience designing and implementing evaluation systems, including LLM-as-Judge frameworks, metric design, synthetic data generation, and agent benchmarking pipelines.
- Expertise in AI/LLM observability and tracing, including instrumentation of systems and analysis of trace data for performance, latency, and correctness (e.g., OpenTelemetry-based tools such as LangFuse or equivalent).
- Experience architecting and deploying enterprise-scale AI systems or subsystems, with the ability to define technical direction, architecture, and reusable platform components across teams.
- Deep expertise in at least one of the following areas: Agent memory systems (context management, long-term persistence, retrieval optimization), AI gateways / tool orchestration layers (e.g., MCP, service integration, authorization, tool discovery), Agentic workflows and orchestration (multi-step planning, tool calling, error recovery, concurrency).
- Demonstrated ability to translate ambiguous problems into scalable AI systems with measurable impact.
- Experience driving engineering standards, improving system reliability, observability, and performance (latency, throughput, cost).
- Strong familiarity with security, privacy, compliance, safety, and auditability in enterprise AI systems.
- Excellent communication and cross-functional collaboration skills; able to influence and align across engineering, product, and other internal teams.
- Proven ability to learn and apply new technologies quickly through hands-on development.
Benefits
- Competitive compensation package
- Snacks, lunches and fun activities
