Manager II, Tech(AI)

BEST is modernizing our data capabilities to accelerate product innovation, data-driven decision making, and AI-enabled experiences.

Today the organization operates with traditional data engineering practices; we are hiring a transformation leader who will modernize the platform, build production-grade ML/AI capabilities, and embed responsible AI across the business.

We’re hiring a strategic, hands-on Sr.

Manager, Data Services to own and scale BEST’s data platform and teams—leading engineers and managers across ingestion, transformation, platform services, data products/APIs, governance, and production ML/AI.

You’ll be accountable for MLOps, model serving, and the people/processes to safely operationalize AI at scale, transforming a traditional data-engineering function into an AI-first, product-oriented organization.

This role requires deep technical expertise in data platforms, MLOps and LLM/AI patterns, plus proven people leadership and cross-functional influence.

• Strategy & Roadmap — Define and operationalize a 12–24 month roadmap for Data Services that supports company data and AI goals (data APIs, platform, governance, ML pipelines, model serving and monitoring).
• Team Leadership — Hire, mentor and grow a high-performing team (data engineers, platform engineers, ML engineers, SREs). Build leadership bench and establish clear career paths.
• Data Platform Ownership — Own the design, delivery, and run-book for data platforms (data lake/warehouse, streaming, ingestion, processing, metadata/catalog, lineage and observability).
• ML/AI Enablement — Partner with AI/ML teams to build repeatable ML pipelines and production model serving (batch & real-time). Lead MLOps adoption: model training, deployment, CI/CD, drift detection, and model governance.
• AI Productionization — Drive production-grade implementations of AI use-cases (including large language models, retrieval-augmented generation, knowledge graphs, agentic/automated workflows). Ensure safe, scalable, and cost-efficient model serving and inference.
• Data Products & APIs — Deliver production data products and APIs consumed by analytics, product teams, and AI systems. Enable self-service data and ML capabilities for downstream teams.
• Quality, Observability & Governance — Implement enterprise-grade data quality, lineage, cataloging, access controls, and privacy/compliance practices. Partner with security and legal on policy for AI model usage and data privacy.