Senior Staff AI Engineer
$244.14k - $413.16kFull-time
XPENG
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. We are looking for a hands-on Senior Staff AI Engineer to build and scale production-grade AI systems that drive measurable impact across internal teams. This role owns the end-to-end delivery of applied AI solutions—partnering with product, engineering, and cross-functional teams across the organization to identify high-value use cases, and translating them into scalable systems using LLMs, retrieval, and agentic workflows. You will also define architecture and reusable patterns to enable AI adoption broadly, while setting a high bar for reliability, evaluation, and performance. Job Responsibilities
- 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.
Vacancy posted 20 days ago
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