Why Equall
Equall is building the legal infrastructure for the private markets — a new system for how corporate legal reality is verified, tracked, and continuously managed.
Our AI-native platform extracts, structures, and reconciles corporate legal information, producing auditable outputs such as a cap table tie-out reports, governance dashboards, and personnel summaries grounded in source documents. Equall executes workflows end to end across both due diligence and day-to-day advisory work, verifying a company's legal state and surfacing actionable issues in real time.
In practice, this means:
Investor-side due diligence delivered in hours, not weeks
Company-side client snapshots, continuously updated
Legal team review reduced by an order of magnitude
This opportunity comes at a pivotal moment in Equall's journey. We are working with leading law firms in ECVC and are now entering a period of rapid growth as we scale both our customer base and our product — extending coverage across the venture and emerging companies ecosystem and expanding into private equity and M&A.
Equall brings together leaders across legal, engineering, and AI to deliver transformative value. We listen closely to our customers, build with purpose, and work with both enthusiasm and a steadfast commitment to excellence — driven to reshape how corporate legal work is executed and how legal ground truth is determined.
If you are interested in playing an impactful role in this mission, we would be excited to hear from you.
The Role
We are seeking an exceptional backend engineer to own the graph systems that sit at the heart of Equall's platform. Our knowledge graph is how we represent corporate legal reality — entities, relationships, documents, and claims — and it is what makes agentic legal workflows possible at scale. You will design the APIs, build the data pipelines, and shape the graph infrastructure that turn unstructured legal documents into structured, queryable, auditable legal ground truth. This is a deep backend role — if you take pride in well-designed APIs, reliable pipelines, and production systems that hold up under load, you will feel at home here.
Our Stack
Python
Prefect for DAG-based orchestration
Neo4j for the knowledge graph
Postgres and Redis for application data and caching
Kubernetes for infrastructure
What You'll Do
Design, build, and scale the graph infrastructure and data pipelines that power Equall's platform
Architect and implement the public APIs that internal services, agents, and customers rely on
Build DAG-based processing on Prefect for extracting, transforming, and reconciling legal data from source documents
Partner with AI researchers and engineers to integrate agentic systems into production workflows
Operate our services on Kubernetes — deployment, observability, and performance
Shape engineering standards and architecture for a fast-growing backend team
What You'll Have
Strong experience building production backend systems in Python, Go, Rust, or Zig
Experience designing and operating data pipelines at scale
Deep familiarity with graph databases like Neo4j — modeling, querying, and running them in production
Strong opinions on the design of public APIs — ergonomics, versioning, and evolvability
Comfort operating services on Kubernetes
Excellent judgment on system design tradeoffs and a bias toward shipping
Bonus Points
Experience building a graph database (not just using one)
Experience designing DAG-based processing or workflow orchestration systems (Prefect, Airflow, Dagster, Temporal, or similar)
Experience building agentic systems or integrating LLM-powered workflows into backend infrastructure
Experience building control systems or other feedback-driven coordination infrastructure
Experience with Kafka or similar event-streaming platforms