- Lead the technical design and hands-on development of prioritized AI applications, services, and platforms leveraging state-of-the-art LLM app stacks, retrieval-augmented generation, evaluation frameworks, and scalable serving.
- Define long-term architecture and engineering standards for Applied AI systems to maximize reuse, reliability, and impact across multiple product areas.
- Partner with business sponsors to translate high-value opportunities into roadmaps and shipped products with clear success metrics and measurable outcomes.
- Build a holistic view of AI investments by collaborating with adjacent engineering groups implementing AI in their domains, aligning patterns, reusing components, and avoiding duplication.
- Drive continuous improvement in AI methodologies and best practices; evaluate emerging capabilities and land them as secure, production-grade systems.
- Collaborate with stakeholders to embed robust governance, privacy, security, safety, and reporting practices across the AI lifecycle.
- Champion AI literacy, enablement, and adoption through demos, guidance, and technical leadership across the organization.
- Establish rigorous evaluation, guardrails, and monitoring practices; instrument offline and online metrics to ensure quality, safety, and SLOs.
- 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.
- Proven ability to establish feedback loops from production systems into evaluation and model improvement workflows.
- 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.
- Experience building custom evaluation harnesses or contributing to open-source harness frameworks.
- Contributions to widely used third-party benchmarks or evaluation suites.
- Hands-on experience developing and evaluating coding agents or code-generation systems.
- Experience working with and deploying open-source language models.
- A fun, supportive and engaging environment.
- Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving.
- Opportunity to work on cutting edge technologies with the top talent in the field.
- Competitive compensation package.
- Snacks, lunches and fun activities.
Skills Required
- BS/MS/PhD in Computer Science or related field
- 10+ years of software engineering experience
- Deep technical expertise in AI/ML
- Hands-on experience building and scaling AI systems
- Strong experience designing evaluation systems
- Expertise in AI observability and tracing
- Experience architecting and deploying enterprise-scale AI systems
- Demonstrated ability to translate ambiguous problems into scalable AI systems
What We Do
Xpeng Motors is a leading Chinese electric vehicle and technology company that designs and manufactures intelligent automobiles that are seamlessly integrated with the Internet and utilize the latest advances in artificial intelligence. Focusing on China’s young and tech-savvy consumer base, XPENG Motors strives to offer smart mobility solutions with technology innovation and cutting-edge R&D. The company’s initial backers include its CEO & Chairman He Xiaopeng, the founder of UCWeb Inc. and a former Alibaba executive. It was co-founded in 2014 by Henry Xia and He Tao, former senior executives at Guangzhou Auto with expertise in innovative automotive technology and R&D. It has received funding from prominent Chinese and international investors including Alibaba Group, Foxconn Group and IDG Capital. Currently with 3,000 employees, the company is headquartered in Guangzhou and has design, R&D, manufacturing and sales & marketing divisions in Silicon Valley, San Diego, Beijing, Shanghai, Zhaoqing (Guangdong Province) and Zhengzhou (Henan Province).









