The Role
Design, build, and operate a production AI engineering platform that connects agents to engineering systems. Build reliable distributed services, automation, agent lifecycle and safe action execution, semantic data layers, and observability. Lead customer onboarding, gather requirements, debug production issues, and drive adoption while establishing evaluation and safety guardrails.
Summary Generated by Built In
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.
You will be a senior engineer on the team building our internal AI engineering platform — the systems, services, and automation that power how our engineers build and ship software. A core mission is connecting agents to real engineering decisions: giving agents a connected, semantic view of our systems and data, and letting them propose and safely execute actions against operational systems. The agentic layer (NL intake, agentic trouble-shooting, task orchestration, auto-research loop) is an important component, but the foundation of this role is strong software engineering: designing robust distributed systems, building reliable services and pipelines, and relentlessly automating manual workflows. You'll also work directly with internal and external customers to understand their workflows and drive adoption.
Job Responsibilities:
- Design, build, and operate production-grade platform services and infrastructure with strong reliability, observability, and performance.
- Identify manual, repetitive engineering workflows and eliminate them through self-service automation on the platform.
- Build and evolve the agentic layer: agent lifecycle, tool/MCP integrations, sandboxed execution, multi-agent workflows.
- 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.
- 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.
- Own system design for new platform capabilities end to end, from requirements through rollout and operations.
- Work directly with customers: lead technical onboarding, gather requirements, debug production issues, and turn field feedback into roadmap priorities.
- Establish best practices for agent evaluation, observability, and safety guardrails.
Minimum Skill Requirements:
- Master's degree in Computer Science, Software Engineering, or related fields.
- 5+ years building and operating production distributed systems, with demonstrated strength in system design and software engineering fundamentals.
- Proficiency in Python and TypeScript; solid grasp of databases, message queues, caching, and API design.
- A builder's instinct for automation: a track record of turning manual processes into tools, pipelines, or self-service systems.
- Hands-on experience with modern AI coding tooling and LLM APIs, including tool use/function calling.
- Experience with agentic systems or task orchestration platforms (workflow engines, multi-agent frameworks, MCP servers, or similar).
- Strong cross-team communication skills.
Preferred Skill Requirements:
- Familiarity with Autonomous Driving terminologies and model development workflows.
- Direct customer-facing experience: solutions engineering, technical onboarding, developer relations, or enterprise support.
- Experience with data/domain modeling: semantic layers, knowledge graphs, or object models over heterogeneous data sources.
- Experience integrating with enterprise or operational systems (internal platforms, legacy APIs, writeback to systems of record).
- Experience with evaluation frameworks and observability for LLM applications.
- Familiarity with sandboxing/isolation technologies.
- Contributions to open-source agent frameworks, MCP servers, or developer tools.
- Experience driving adoption of developer tooling within engineering organizations.
What do we provide:
- 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.
The base salary range for this full-time position is $174,720 - $295,680, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.
Skills Required
- Master's degree in Computer Science, Software Engineering, or related field
- 5+ years building and operating production distributed systems with strong system design skills
- Proficiency in Python
- Proficiency in TypeScript
- Solid grasp of databases, message queues, caching, and API design
- Track record of automating manual engineering workflows into tools, pipelines, or self-service systems
- Hands-on experience with modern AI coding tooling and LLM APIs, including tool use/function calling
- Experience with agentic systems or task orchestration platforms (workflow engines, multi-agent frameworks, MCP servers)
- Strong cross-team communication skills
- Familiarity with autonomous driving terminologies and model development workflows
- Direct customer-facing experience (solutions engineering, technical onboarding, developer relations, enterprise support)
- Experience with data/domain modeling, semantic layers, or knowledge graphs
- Experience integrating with enterprise or operational systems and writeback to systems of record
- Experience with evaluation frameworks and observability for LLM applications
- Familiarity with sandboxing/isolation technologies
- Contributions to open-source agent frameworks, MCP servers, or developer tools
- Experience driving adoption of developer tooling within engineering organizations
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
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).
.png){kind=logo}
