Senior / Staff Data Platform Engineer (AI)

Location: New York City preferred, with flexible location arrangements; up to 8 weeks per year working from anywhere.

Company

AI-native legal tech platform turning complex corporate transaction data into structured, searchable market intelligence for legal and finance professionals.

What you will do

• Design, build, and optimize pipelines that ingest, transform, and distribute high-volume legal and financial document data.
• Build reliable, high-performance backend services and APIs for document storage, retrieval, and processing.
• Implement data governance, privacy controls, audit trails, and regulatory compliance, including GDPR.
• Lead database migrations and improve schema design, query performance, and scalability.
• Partner with ML and AI teams on model training, evaluation, and inference at scale.
• Mentor engineers on architecture, system design, and engineering practices; at Staff level, own the technical roadmap, architecture decisions, technology selection, infrastructure strategy, and platform team development.

Requirements

• Senior: 7+ years in software engineering, including 4+ years focused on data platforms, backend infrastructure, or related systems, plus experience mentoring engineers.
• Staff: 10+ years in software engineering, including 6+ years focused on data platforms or infrastructure, experience architecting high-throughput systems at petabyte scale or similar complexity, and a track record of building and mentoring teams and completing complex technical initiatives.
• Strong production experience in Python; Java, Go, C++, or Rust are also valued.
• Experience with distributed systems and large-scale data technologies such as Spark, Hadoop, Snowflake, or modern data platforms.
• Strong SQL and NoSQL skills, including data modeling and query optimization.
• Experience with scalable API design and backend service development.
• Experience with AWS, GCP, or Azure and infrastructure as code.
• Experience with data compliance, privacy engineering, and secure data handling in regulated environments.
• Sound judgment when balancing quality, speed, cost, and risk.

Nice to have

• Experience in legal tech, financial services, or another highly regulated industry.
• ML infrastructure experience, including ML pipelines, feature stores, or platforms supporting AI workloads.
• Experience with real-time and streaming data, including Kafka or Flink.
• Experience leading major architectural transitions or platform migrations.
• Experience in a high-growth environment where the platform was critical to the business.
• Technical writing or speaking experience on data systems or architecture.

Culture & Benefits

• Startup pace and team structure with the data, distribution, and resources of a global enterprise parent company.
• Flexible work, including up to 8 weeks per year working from anywhere.
• Flexible vacation.
• Retirement savings, tuition reimbursement, and wellbeing support.
• Ownership of core platform infrastructure supporting an AI product used by legal and finance professionals.