Key Facts

Remote From:

Austria, Colorado (USA), United States

Full time

English

Hard Skills

Other Skills

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Collaboration
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Communication

Roles & Responsibilities

Strong Python engineering skills (production-quality code, testing, debugging)
Hands-on applied ML experience, especially NLP / document AI
Experience with LLM integration (prompting, structured output, tool/function calling, retrieval)
Comfortable owning features end-to-end: from prototype → production → iteration

Requirements:

Build, maintain, and scale document ingestion + processing pipelines (PDFs, structured/unstructured docs)
Integrate and productionize LLM-powered workflows (extraction, classification, summarization, validation)
Improve accuracy, reliability, and cost/performance of models and pipelines
Collaborate with product and engineering to turn customer needs into shipped features

25madison

Private Equity & Venture Capital

About 25madison

25madison is a Venture Platform, co-incubating ideas, investing in early-stage startups, and propelling brands into their next phase of growth. 25m Studio is crafting companies from scratch. Strategy, brand, product, engineering, operations - we do it all. (25madison.com/studio) 25madison Ventures Fund I is investing Pre-Seed to Series A in category-defining startups. (25madison.com/ventures) 25m Health is a Healthtech Venture Studio and unique partnership to find and develop innovative solutions that make communities healthier. (25madison.com/health) 25m Create is a brand and experience agency. We're creating transformative brands. We think and act like founders, partnering with you to build a brand experience that positions your company for growth. (25madison.com/create) Let’s do big things.

Company type: Scaleup

Industry: Private Equity & Venture Capital

Founded: 2018

Company size: 11 - 50

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Job description

Applied AI Engineer

Company: Stealth Co.

Role: Applied AI Engineer (Full-time)

Location: Remote (US, must have US Work Authorization)

Who We Are: We’re building the AI-native operating system for litigation. Today, legal teams face millions of siloed documents across PDFs, emails, and spreadsheets—making facts hard to connect and knowledge fragile. Our platform turns this chaos into knowledge graphs rooted in structured ontologies, compounding insights with every case. The result: faster strategy, stronger arguments, and a lasting edge in high-stakes litigation.

About the Role: We’re hiring an AI Engineer to build and scale document processing pipelines, integrate LLMs, and ship AI-powered product features. You’ll work on real production systems where Legal Tech meets practical AI productization.

What you’ll do

Build, maintain, and scale document ingestion + processing pipelines (PDFs, structured/unstructured docs)
Integrate and productionize LLM-powered workflows (extraction, classification, summarization, validation)
Improve accuracy, reliability, and cost/performance of models and pipelines
Collaborate with product and engineering to turn customer needs into shipped features
Add evaluation, monitoring, and feedback loops to continuously improve outputs

Qualifications

Strong Python engineering skills (production-quality code, testing, debugging)
Hands-on applied ML experience, especially NLP / document AI
Experience with LLM integration (prompting, structured output, tool/function calling, retrieval)
Comfortable owning features end-to-end: from prototype → production → iteration
Product-focused mindset (shipping, measuring impact, iterating fast)

Nice to haves:

Experience with OCR, layout parsing, entity extraction, or citation/provenance workflows
Familiarity with cloud infrastructure and deployment (e.g., Docker, Cloud Run, AWS/GCP)
Experience building evaluation harnesses for LLM quality (gold sets, metrics, regression testing)
Prior work in legal tech, compliance, or other high-accuracy domains

To apply, submit your resume via breezy. Applications will be accepted on a rolling basis.

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