Backend Engineer, Foundations

Backend Engineer, Foundations

Backend Engineer, Foundations

The company is building the operating system for legal risk by combining AI-native workflows, knowledge graphs, legal ontologies, and multi-step agentic systems to automate complex legal analysis at enterprise scale.

Its platform transforms unstructured legal documents into structured, queryable legal intelligence, enabling enterprise customers to perform legal diligence, risk analysis, and document understanding in real time. By combining large language models, knowledge graphs, distributed data pipelines, and modern backend infrastructure, the company is redefining how legal work is performed.

Founded by top law firm partners alongside world-class AI researchers and engineers, the company is assembling a small, elite engineering team to build foundational infrastructure powering the next generation of AI-native legal software.

As a Backend Engineer, Foundations, you'll own the company's core backend infrastructure, knowledge graph architecture, distributed data pipelines, and backend services while partnering closely with AI researchers and platform engineers to build production-grade AI systems that power enterprise legal workflows.

This is an exceptional opportunity to join an AI-native startup where backend engineers own foundational platform architecture, influence technical direction, and build the core infrastructure supporting one of the most ambitious legal AI platforms in the market.

• Design, build, and scale the knowledge graph infrastructure powering the company's AI platform
• Architect distributed backend systems for processing large volumes of legal documents
• Build scalable data ingestion, transformation, and reconciliation pipelines using DAG-based workflows
• Design and develop production APIs supporting internal services, AI agents, and enterprise customers
• Build backend services using Python and modern distributed systems technologies
• Design scalable data architectures using Neo4j, PostgreSQL, Redis, and related technologies
• Develop workflow orchestration systems using Prefect and similar orchestration frameworks
• Operate and optimize Kubernetes infrastructure supporting production AI workloads
• Improve platform scalability, reliability, observability, and operational performance
• Partner closely with AI researchers to integrate agentic AI systems into production environments
• Establish engineering best practices across backend architecture, security, and platform reliability
• Continuously improve distributed systems supporting enterprise-scale legal AI workloads

• 3+ years of backend software engineering experience
• Experience building production backend systems at scale
• Experience working at fast-moving startups or high-growth technology companies
• Experience designing scalable distributed backend architectures
• Experience owning backend infrastructure with significant engineering impact
• Experience building APIs and data-intensive backend services
• Experience working with large-scale data processing pipelines
• Strong startup ownership mentality with demonstrated engineering execution
• Experience operating production infrastructure in cloud environments preferred
• Experience collaborating closely with AI or platform engineering teams preferred

• Strong backend engineering experience using Python
• Experience building scalable distributed systems
• Strong understanding of databases, data modeling, and system architecture
• Experience with PostgreSQL and Redis
• Experience working with Kubernetes in production
• Experience building workflow orchestration systems using Prefect, Airflow, Dagster, Temporal, or similar tools
• Experience designing production APIs and backend services
• Strong software engineering fundamentals across scalability, reliability,…