LITMAS AI
https://litmas.aiAbout
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NodeJS (Node.js)
MongoDB
NextJs (Next.js)
PythonFounding Engineer - LITMAS
About LITMAS
LITMAS is revolutionizing litigation with the first AI-powered platform built specifically for elite litigators. We're transforming how attorneys research, strategize, draft, and win cases by combining comprehensive case repositories with cutting-edge AI validation and workflow automation. We are a team incubated by experienced litigators, building the future of legal technology.
The Opportunity
We're seeking a Founding Engineer to join our core team and shape the technical foundation of LITMAS. This is a rare opportunity to build a category-defining product from the ground up, working directly with the founders to create technology that will transform the US litigation market.
As a founding engineer, you'll have significant ownership over our technical architecture, product decisions, and company culture. Your code will directly impact how thousands of attorneys practice law.
What You'll Do
- Architect and build core platform features using Python, Node.js, Next.js, React, and MongoDB
- Design and implement production-grade LLM systems with advanced tool usage, RAG pipelines, and agent architectures
- Build AI workflows that combine multiple tools for legal research, validation, and document analysis
- Create scalable RAG infrastructure to handle thousands of legal documents with high accuracy
- Implement AI tool chains to provide agents tool inputs
- Design intuitive interfaces that make complex legal workflows simple and powerful
- Own end-to-end features from conception through deployment and iteration
- Establish engineering best practices for AI systems including evaluation, monitoring, and safety
- Collaborate directly with founders on product strategy and technical roadmap
The Ideal Candidate
You're not just an AI engineer, you're someone who understands how to build reliable, production-grade AI systems that users can trust. You've wrestled with RAG accuracy, tool reliability, and LLM hallucinations in production. You know the difference between a demo and a system that handles real-world complexity. You're excited about applying AI to transform how legal professional’s work.
What We're Looking For
Must-Haves
- Deployed production-grade LLM applications with demonstrable experience in:
- Tool usage and function calling
- RAG (Retrieval-Augmented Generation) implementation at scale
- Agent architectures and multi-step reasoning
- Prompt engineering and optimization
- Knowledge of multiple LLM providers (OpenAI, Anthropic, Cohere, open-source models)
- Background in building AI evaluation and monitoring systems
- Experience with document processing and OCR technologies
- 3+ years of production experience with Node.js, Python, Next.js, and React
- Strong MongoDB expertise including schema design and optimization
- Experience with vector databases (Pinecone, Weaviate, Qdrant, or similar)
- Full-stack mindset with ability to own features from database to UI
- Track record of shipping complex web applications at scale
- Deep understanding of LLM limitations, hallucination prevention, and validation techniques
Tech Stack
- Backend: Node.js, Express, MongoDB
- Frontend: Next.js, React, TypeScript, Modern CSS
- AI/ML: LangChain/LlamaIndex, OpenAI/Anthropic APIs, vector databases, custom AI tools
- Additional: Document processing, search infrastructure, real-time collaboration
What We Offer
- Significant equity stake true ownership in the company you're building
- Competitive compensation commensurate with experience
- Direct impact your decisions shape the product and company
- Learning opportunity work with cutting-edge AI and legal technology
- Flexible work remote-first with a global team
- AI resources access to latest models and compute resources
Interview Process
One more thing: Our process includes deep technical interviews and fit conversations. As part of the evaluation, there will be an extensive take-home test that should expect to take at least 4-5 hours depending on your skill level. This allows us to see how you approach real problems similar to what you'll encounter at LITMAS.
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