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At Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. Harvey is building the future of legal work, and we’re looking for an Engineering Manager to help lead the charge. Our Document Platform team sits at the core of our platform—enabling our AI systems to make sense of massive troves of legal documents. From OCR to vector storage, our systems must be fast, accurate, and scalable to meet the demands of the top law firms in the world. You’ll lead a team of exceptional engineers to extend our capabilities, push the boundaries of what’s possible in document understanding, and ensure our infrastructure scales with our users.
Job Responsibility:
Lead and grow a team of world-class engineers working on document ingestion, understanding, and retrieval
Define and execute a long-term technical roadmap for our document processing systems that aligns with Harvey’s product vision and the needs of our customers
Collaborate closely with Product, Infrastructure, and Applied AI teams to design robust systems that bridge cutting-edge research and production readiness
Stay hands-on: unblock engineers, participate in architecture reviews, and dive into code when needed
Cultivate a culture of engineering excellence, thoughtful experimentation, and continuous improvement
Requirements:
2+ years of experience in a software engineering management role, leading backend teams operating in technically complex domains
A track record of leading high-performing, engaged engineering teams
A strong foundation in backend systems, with 5+ years of hands-on experience designing and operating distributed systems in a cloud environment
Ideally, direct experience in architecting or scaling document ingestion and processing, search systems, or data infrastructure (e.g. OCR pipelines, Elasticsearch, vector databases)
Nice to have:
Ideally, direct experience in architecting or scaling document ingestion and processing, search systems, or data infrastructure (e.g. OCR pipelines, Elasticsearch, vector databases)