Software Engineer - Wexler
pear-vc · Remote
Experience: lead
About Wexler Wexler is building the best AI system for litigation on the planet. We work with some of the world’s largest law firms, helping them to solve their most complex cases, find the winning strategy in each matter, and create clarity from the chaos of documents and facts in each case. We are a rapidly growing, legal AI company based in London. Clifford Chance, HSFKramer, Goodwin, Addleshaw Goddard and more rely on us to help find the critical facts that can determine their chances of winning a case. We’re backed with a $5.3M Seed by Pear VC, Seedcamp, The LegalTechFund + many leading industry angels. We are building a comprehensive AI platform for managing, resolving and preventing legal disputes across Enterprise law firms and Fortune500 companies. We are growing 10x YoY and signing more eminent firms every month. Our system extracts, objective, cross referenced facts from millions of documents, helping litigators win more cases whilst saving months of working hours. In this way we ensure every client gets the representation they deserve. AI is transforming the law, but most tools have focused on contract law or are generalist copilots that aggregate the tasks lawyers do across practices. Wexler is the leading gen-AI platform specifically built for the nuances of litigation, and our growth proves the story is resonating. About the Role We're seeking an entrepreneurial full-stack engineer who will work closely with the founders to architect, build and scale Wexler's agentic systems for document analysis, powered by our state-of-art fact extraction engine. As a Software Engineer, you will work closely with the founding technical team and contribute to the technical architecture of our product and delivery of our ambitious product roadmap. You'll play a key role in shaping the culture of our Technical organisation and will learn alongside expert Software and Machine Learning Engineers. You will rapidly take on more responsibility and have a clear path to a lea