Senior Product Manager, Translation Quality & Platform

This is a permanent, full-time role that begins by taking on an existing PM's translation quality, expert-experience, and analytics work during leave, then evolves with business priorities and team capacity. The PM will serve as the single directly responsible individual for AI Review, AI QA, and the expert and linguist experience.

Responsibilities

Own the roadmap, tradeoffs, and delivery sequencing for translation quality, the expert and linguist experience, and customer-facing reporting experiences; Lead product delivery for AI Review and AI QA from problem definition through evaluation, requirements, UAT, and release; Define product evaluation questions and acceptance criteria, partnering on benchmarks and sampled human evaluations; Own the product roadmap and reporting experience for customer-facing analytics on translation quality, turnaround time, spend, and usage; Own product improvements to tools used by experts and linguists to review, assess, and deliver translations; Lead technical conversations on quality, analytics, and the expert and linguist experience, and act as a product point of contact for customers; Write PRDs, acceptance criteria, and UAT plans, and communicate decisions, progress, and release notes; Take ownership of selected Broader Platform initiatives such as workflow automation, admin settings, permissions, or account structures

Requirements

Hands-on builder mindset and AI fluency, using AI and agentic workflows to accelerate discovery, evaluation, analysis, requirements, documentation, and troubleshooting; AI evaluation and LLM product experience, including test sets, precision and recall, acceptance rates, latency, cost, and error scoring; Data and analytics fluency, including SQL or similar tools, defining metrics, and turning customer reporting needs into data requirements; Production and quality grounding, including understanding of linguist workflows, review stages, and quality programs; Product judgment and ownership, including prioritizing a multi-customer backlog, writing specifications and acceptance criteria, and driving ambiguous work to closure; Customer presence, leading discovery and troubleshooting directly with enterprise customers (essential requirement); Clear communication across technical and non-technical teams

Nice to have

Background in localization production, operations, or language quality before moving into product, including structured linguistic quality evaluation programs such as Multidimensional Quality Metrics (MQM) and terminology management; Experience with embedded analytics or BI tools in a B2B SaaS product; Experience supporting AI features in high-assurance or regulated environments, including subprocessor and data-processing requirements; Experience with platform product work, such as admin settings, user permissions, APIs, or account structures; Experience introducing AI-enabled operating practices across product and engineering teams, with measurable improvements in speed or quality