23 days ago
Base Salary
$123k - $178k/yr
Responsibilities
- Build and productionize GenAI/LLM solutions for data-engineering workflows such as code and SQL assistance, metadata and lineage discovery, data retrieval, and engineering knowledge access.
- Develop retrieval/RAG and agentic workflows connecting documentation, SOPs, databases, metadata, logs, APIs, and internal platforms with evaluation, guardrails, and access controls.
- Automate incident triage, log and alert analysis, root-cause analysis, and repeatable data-engineering workflows.
- Integrate AI capabilities into reusable internal services and developer tools, including monitoring, feedback loops, quality metrics, and adoption measures.
- Partner with Data Engineering, AI, SRE, Database, Platform, and global teams to identify use cases and integrate solutions into existing workflows.
- Own projects from problem definition through implementation and production support while contributing to engineering standards and documentation.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or an equivalent technical discipline.
- 3+ years of software, machine learning, data, or platform engineering experience with hands-on ownership of production systems, services, or developer-facing tools.
- Strong Python and SQL skills with solid software-engineering fundamentals and practical knowledge of databases, APIs, data pipelines, and distributed systems.
- Hands-on experience building GenAI/LLM applications using retrieval/RAG, embeddings, tool or function calling, agents, prompt workflows, or model APIs.
- Experience productionizing services, automation, or data/ML workloads with testing, CI/CD, monitoring, logging, security considerations, and incident troubleshooting.
- Strong ownership and communication skills, including the ability to translate ambiguous engineering problems into focused, measurable solutions and collaborate with distributed teams.
- Preferred experience with Spark, Flink, Kafka, Hive or lakehouse systems, Airflow, Kubernetes, metadata and lineage, enterprise search, observability, incident/RCA automation, cloud-scale data platforms, Paimon, Iceberg, Delta Lake, internal AI-tool adoption, or high-scale e-commerce and data-platform environments.
Benefits
- Bonus eligible.
- Medical, dental, vision, prescription-drug coverage, a Health Savings Account with employer funding, and Flexible Spending Accounts.
- Company-paid basic life/AD&D insurance, short- and long-term disability, and additional voluntary insurance offerings.
- Employee Assistance Program, Business Travel Accident Insurance, and a 401(k) savings plan with discretionary company match and access to a financial advisor.
- Vacation, paid holidays, floating holidays, and sick days.
- Employee discounts, free weekly catered lunch, office snacks and beverages, free swag, and annual company events.
- Dog-friendly offices and free gym access are available at select locations.
Tech Stack
Categories
AI ApplicationsData Engineering
About SHEIN
SHEIN is a global online fashion and lifestyle retailer that sells apparel, accessories, beauty, and home goods through its website and mobile app. It combines its own SHEIN-branded lines with products from a broad vendor network, using on-demand production and cross-border fulfillment to release styles quickly. Founded in 2012 and headquartered in Singapore, it is privately held and operates design and logistics hubs worldwide.