• Own the full product loop independently: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement. You are accountable for the outcome, not just the handoff. • Conduct customer discovery and use AI tools to synthesize research across tickets, interviews, behavioral data, and competitive signals. • Demonstrate deep functional and technical knowledge of owned products end-to-end. Demo to merchants and partners; understand competitive landscape and key differentiators. • Use AI tools to analyze product metrics, identify usage patterns, and surface anomalies. Define success metrics and kill thresholds at spec time without coaching. • Maintain a prioritized roadmap ranked by impact × speed. Use AI tools to synthesize competitive intelligence, market trends, and customer insight into strategic inputs. • Evaluate whether a proposed solution fits ShipBob's architecture without Engineering translation. Understand service boundaries, data structures, and how merchant and partner API usage shapes data contracts. • Route changes through prototype-then-PR. Write clear story/specs and review AI-generated code before raising. PR promotion rate improves consistently. • Set experiment hypotheses with explicit kill thresholds. Make day-7 rollout/kill decisions on AI-surfaced data. • Additional duties and responsibilities as necessary. • You'll apply this builder model to one of ShipBob's most operationally critical product surfaces – Sortation Technology. • Translate merchant, marketplace, and channel requirements into sortation capabilities across the fulfillment lifecycle. Sortation performance shapes outcomes for DTC, marketplace, B2B/retail, and returns flows: on-time shipping, marketplace and retailer routing-guide compliance, inventory accuracy, and accurate returns disposition. Sequence the roadmap around the highest-impact pain points. • Close the gap between system signals and physical reality across every sortation surface. Sortation failures show up as merchant-visible defects: late shipments, mis-sorts, missing tracking events, mis-routed returns, and inventory inaccuracy at stowing. Build the tooling, workflows, and verification signals that prevent them. • Partner with Operations to turn product into adoption. Work directly with FC, Sort Center, Inbound, and Returns leadership, alongside Process Engineering and Transportation. Translate new tools into standard operating procedures and measurable performance improvement across every sortation surface — from manual sort to future automated unit sorters. • Move the metrics that define sortation performance — outbound execution SLAs (Click-to-Collect, Mis-sort Rate, Container Audit Defect Rate), inbound rebuild outcomes (drop-to-stock, SLA adherence), B2B compliance (SLA, load accuracy, retailer routing-guide compliance), and returns processing (cycle time, disposition accuracy).

• Assume end-to-end ownership of key strategic initiatives in AI/automation/innovation. • Develop a strong understanding of Escalent groups products, tools, solutions, and technological roadmap. • Demonstrate capability to link findings and recommendations to desired business impact. • Present findings and recommendations to senior/executive leadership. • Scope out research-focused AI products/features/agents with a clear understanding of the use case. • Work with industry/methodology/technique SMEs to chalk out the product workflow. • Co-develop the development/implementation and scaling plan in collaboration with tech, development, and product teams. • Craft and co-implement alpha and beta testing plans, and rollout roadmaps. • Own the feature and scaling roadmap, and hold teams accountable for their tasks and timelines. • Organize and administer demos, show-n-tells, and lunch-n-learns.

• Labelling, annotating, and evaluating content in Korean • Evaluating AI-generated content for quality • Building Korean-specific datasets • Delivering labelled assets on time • Collaborating with Data Labelling teams

• Labelling, annotating, and evaluating photos in Thai • Evaluating AI-generated content for Thailand users • Building Thailand-specific datasets for AI features • Delivering labelled assets on time across task types • Collaborating with in-house Data Labelling teams for alignment