LawPay

Software Engineer, Level 6

LawPay

full-time

Posted on:

Location: 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSCloudPython

About the role

  • Collaborate with product managers and stakeholders to translate business problems into AI-driven solutions.
  • Design, implement, and integrate AI features into existing 8am products to enhance and expand the product suite.
  • Partner with the Data team to ensure the right data is collected, enriched, prepared, and staged for AI consumption and use.
  • Build and evaluate AI-powered services, from customer-facing prototypes to general availability to all our customers.
  • Write high-quality Python code to manipulate data, interact with large language models, and assess performance.
  • Develop tools and infrastructure to support reliable, scalable, and secure AI deployment.
  • Work with our cloud operations team to deploy AI features, monitor their impact, and continuously improve them.
  • Deliver on the roadmap of AI features to create new capabilities and strengthen our platform.

Requirements

  • 5+ years of professional software engineering experience, ideally in full stack SaaS application development or backend.
  • Proven track record of building and deploying production-ready AI/ML services.
  • Hands-on experience with LLM frameworks, platforms and related tooling.
  • Strong Python development skills and familiarity with data manipulation and evaluation workflows.
  • Experience building scalable data infrastructure and integrating models into broader SaaS systems.
  • Experience working in AWS cloud environments and with modern DevOps practices.
  • Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field (preferred).
  • Experience fine-tuning and optimizing Large Language Models (LLMs) (preferred).
  • Experience integrating AI into streaming or real-time data flows (preferred).
  • Background in Natural Language Processing (NLP) (preferred).
  • Exposure to fintech or the legal industry (preferred).
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