Note: The job is a remote job and is open to candidates in USA. Motorola Mobility, a Lenovo Company, is a global technology powerhouse focused on delivering Smarter Technology for All. The Advisory AI Software Engineer will be responsible for end-to-end engineering implementation, global cloud deployment, and full-stack system optimization of Lenovo’s enterprise AI systems.
Responsibilities
- Back-End Service Development: Based on the enterprise AI agentic system technical specifications and Reference Design, build enterprise-level distributed services using mainstream technical stacks; design and develop APIs and SDKs, implement core business logic, and ensure the high availability, high scalability and high performance of back-end services for AI agentic systems
- Full-Stack System Integration: Complete front-end interface development and human-computer interaction design for AI products (adapted to PC/mobile/cloud terminals); realize seamless data interaction and full-stack integration between front-end applications and back-end services, and ensure the fluency and usability of the entire system
- Hybrid Cloud & Edge-Cloud Deployment: Combine Lenovo’s hybrid cloud technical architecture, complete containerization and orchestration of AI products based on Docker/K8s; implement global deployment on public cloud (AWS/Azure), private cloud and edge devices, and solve cross-regional deployment environment compatibility, network latency and resource scheduling problems
- System Performance Optimization: Optimize the running performance of AI products from the engineering level, including back-end service tuning, database query optimization, cache strategy design and front-end rendering optimization; reduce system latency, improve throughput, and adapt to the hardware performance characteristics of Lenovo’s end devices/servers to achieve optimal running effect
- Deployment Documentation & Post-Delivery Maintenance: Compile detailed technical documents including product deployment manuals, operation guides and maintenance specifications; provide technical support for the post-delivery operation of enterprise AI products, track system real-time running status, and carry out version iteration and function optimization according to business needs and technical updates
Skills
- Minimum 5 years of Python backend development experience; proficient in asynchronous programming (asyncio) and high-concurrency I/O models
- Hands-on experience building gateway services with FastAPI or Starlette; familiar with streaming output technologies including SSE, WebSocket and NDJSON
- Skilled in Pydantic, type annotations and rigorous type checking workflows (mypy strict mode)
- Well-versed in Python engineering standards: pytest, asynchronous testing, packaging & release (pyproject), dependency and version management
- Experienced in operation and maintenance of mainstream middleware, at minimum Redis and PostgreSQL; solid production knowledge covering connection pools, transactions & data consistency, index optimization, timeout & retry logic, idempotent design, fault recovery and data migration
- Practical Docker containerization experience; capable of independently building images, optimizing runtime parameters and implementing environment isolation
- Proficient with Docker Compose for building and maintaining multi-service local and test environments
- Familiar with Linux development and deployment environments; able to write Shell scripts for automation of build, deployment, troubleshooting and log collection
- Mandatory Vue frontend development skills; able to independently develop admin dashboards and debugging pages, conduct API joint debugging and troubleshoot issues
- Strong system design and problem diagnosis capabilities, able to resolve complex cross-module and cross-service failures
- Familiar with LangGraph or equivalent graph orchestration frameworks; experience designing state machines or workflow engines
- Production observability implementation experience, proficient in OpenTelemetry (traces, metrics, context propagation)
- Engineering experience building LLM applications, with deep understanding of multi-Agent orchestration, tool calling, structured output validation and correction mechanisms
- Experience integrating vector search and memory modules (pgvector, ONNX Runtime, tokenizers, etc.)
- Hands-on experience with Langfuse or comparable evaluation & observability platforms
- Multilingual development proficiency in Java / Python / C++
- Experience maintaining open-source projects, including versioning strategies, compatibility maintenance, documentation and sample code development
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