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Applied AI Engineer — Legal (Remote — Worldwide)
FeaturedLLMsPythonVector DatabasesRAG ArchitectureNLPPostgreSQLPyTorchPrompt EngineeringLangChainModel Evaluation
About the role
As an Applied AI Engineer at Harvey, you will be at the forefront of the legal industry's AI revolution, building the platform that the world’s most elite law firms and legal departments use for complex analysis and workflow automation. You will design and deploy sophisticated LLM-powered systems that handle high-stakes legal reasoning, document generation, and multi-step research tasks with unparalleled precision. Joining our engineering team means solving novel problems at the intersection of large language models and professional-grade legal intelligence to redefine how legal work is performed globally.
Responsibilities
- Design, implement, and optimize RAG pipelines to enable high-accuracy retrieval over massive, private legal datasets.
- Develop and maintain sophisticated agentic workflows that can navigate complex legal documents and provide cited, verifiable answers.
- Fine-tune open-source and proprietary models to improve domain-specific performance for legal drafting and reasoning.
- Build robust evaluation suites to measure and mitigate hallucinations, ensuring the highest level of trust for legal professionals.
- Collaborate with product and legal experts to translate complex legal requirements into technical AI architectures.
- Scale our AI infrastructure to support low-latency inference and high-throughput document processing.
- Stay current with the latest breakthroughs in NLP and LLM research to integrate cutting-edge techniques into our production environment.
Requirements
- 4+ years of experience building and scaling production-grade machine learning or software systems.
- Proven track record of deploying LLM-based applications using frameworks like LangChain, LlamaIndex, or custom orchestration layers.
- Deep understanding of prompt engineering, fine-tuning methodologies, and RAG (Retrieval-Augmented Generation) architectures.
- Strong proficiency in Python and experience with modern backend stacks (PostgreSQL, Redis, Vector Databases).
- Experience evaluating model performance using custom benchmarks and automated evaluation frameworks.
- Ability to work autonomously in a fast-paced, remote-first environment across multiple time zones.
- Passion for legal technology and a high bar for data privacy, security, and output reliability.
Benefits
Equity, healthcare, learning budget.
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