Language Engineer

About Us

At xMentium, we help enterprises turn their unstructured language and documents into structured, usable data at scale. Our AI-powered platform, anchored by xTract, transforms sprawling repositories of contracts, licenses, technical documentation, communications, and other business-critical documents into clean, queryable metadata that powers analytics, agents, and downstream systems.

We work across industries, including media and entertainment, oil and gas, manufacturing, real estate, financial services, and enterprise AI transformation more broadly, helping customers ground their AI agents, accelerate due diligence, unlock the value trapped in legacy repositories, and finally make their documents work for them.

Our team combines deep subject matter expertise with AI, NLU, and language engineering to deliver solutions that are ambitious yet practical.

About the Role

As a Language Engineer at xMentium, you'll be at the forefront of how enterprises curate, structure, and operationalize their most important content. You'll play a pivotal role in bridging the gap between subject matter experts and technology, designing and implementing extraction schemas, configuring AI-powered workflows, and delivering structured data that powers analytics, agents, and enterprise decision-making across a wide range of industries and use cases.

Responsibilities

• Implement and configure xMentium's AI-powered platform to extract structured data at scale from unstructured documents across industries such as media and entertainment, oil and gas, manufacturing, real estate, and more.
• Partner with customers to define extraction schemas, taxonomies, and business rules that turn their document repositories into clean, queryable, machine-readable data.
• Collaborate with software developers, customers, and product managers to define requirements, scope, and design of new platform capabilities.
• Analyze customer processes and workflows to identify high-value opportunities for AI-driven automation and structured data extraction.
• Support sales efforts with software demos and working sessions tailored to the customer's domain and data.
• Lead testing, validation, and quality assurance (including human-in-the-loop review of extraction outputs) to ensure reliability and customer trust.
• Provide training and support to users, facilitating adoption and offering technical assistance as needed.
• Stay current on advancements in AI, LLMs, VLMs, OCR, and enterprise data platforms to continuously improve our offerings.
• Gather user feedback and recommend enhancements to functionality, extraction quality, and overall platform usability.