Senior Product Manager, Translation Quality & Platform

LILT

13d

About The Position

LILT is seeking a Senior Product Manager on its Product team to improve translation quality, the expert and linguist experience, and customer-facing analytics, while taking ownership of selected initiatives across the broader platform. The role combines product judgment, hands-on AI and agentic fluency, data skills, and customer-facing leadership. The position owns AI Review, AI QA, the expert and linguist experience, and product requirements for quality measurement and evidence. It also owns customer reporting needs, reporting experiences, and prioritization for customer-facing analytics, partnering with Data Engineering on underlying data capabilities. The role works closely with Engineering, Applied AI and Research, Production, Quality, Customer Engineering, Customer Success, Forward-Deployed Engineering, and customers. This is a permanent, full-time role. It begins by taking on an existing product manager's translation quality, expert-experience, and analytics work during leave, then evolves according to business priorities and team capacity. The role is open to candidates based in the United States or the United Kingdom; visa sponsorship is unavailable.

Requirements

Demonstrated hands-on use of AI and agentic workflows to accelerate discovery, evaluation, analysis, requirements, documentation, and troubleshooting; able to write and test prompts, run analyses, and build lightweight prototypes or tools when useful.
Able to evaluate AI outputs critically while retaining judgment and accountability; production implementation remains with Engineering.
Understanding of how to measure AI features using test sets, precision and recall, acceptance rates, latency, cost, and error scoring, and to distinguish quality gains from noise.
Ability to explain tradeoffs across quality, speed, reviewer effort, and economics to non-technical stakeholders.
Comfort with SQL or similar tools, defining metrics, and translating customer reporting needs into clear data requirements.
Understanding of translation production, including linguist workflows, review stages, quality programs, and common points of failure.
Ability to prioritize a multi-customer backlog, write clear specifications and acceptance criteria, sequence work against capacity, distinguish isolated issues from systemic problems, and drive ambiguous work to closure.
Ability to learn unfamiliar product areas quickly and take ownership of initiatives beyond an established specialty.
Ability to lead discovery and troubleshooting directly with enterprise customers and communicate complex details to localization managers, administrators, and business stakeholders.
Ability to produce concise decisions, plans, status updates, documentation, and release notes for technical and non-technical teams.

Nice To Haves

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.

Responsibilities

Own the roadmap, tradeoffs, and delivery sequencing for translation quality, the expert and linguist experience, and customer-facing reporting; keep intake, backlog, status, risks, and customer impact current.
Lead AI Review and AI QA product delivery from problem definition through evaluation, requirements, user acceptance testing, and release.
Set quality, latency, cost, and reviewer-effort targets for features, and use evidence to guide release decisions.
Define product evaluation questions and acceptance criteria with Research, Applied AI, and Quality; translate evaluation results into product decisions and clear customer-facing evidence.
Own the product roadmap and reporting experience for translation quality, turnaround time, spend, and usage; define metrics and acceptance criteria and validate that reporting is accurate, understandable, and useful.
Improve tools and experiences used by experts to review, assess, and deliver translations, reducing friction and supporting effective human–AI collaboration.
Lead customer discovery and technical conversations on quality, analytics, and the expert and linguist experience; partner on product escalations and coordinate legal, security, or data-processing questions with the appropriate teams.
Write product requirements documents, acceptance criteria, and UAT plans; lead UAT and release readiness; communicate decisions, progress, and release notes.
Take ownership of selected broader Platform initiatives as priorities and capacity allow, with scope agreed with Product leadership and relevant product owners.
Use AI and agentic workflows to accelerate product discovery, evaluation, analysis, requirements, documentation, troubleshooting, and cross-functional execution.