Company Description QuantEnt Technologies is building enterprise control infrastructure for complex and regulated organizations. Our platform applies quantitative models, graph-based reasoning, advanced mathematics, and AI-native governance to help enterprises understand access, authority, risk, data meaning, and AI-driven action.
Antes de solicitar este puesto, por favor, lea la siguiente información sobre esta oportunidad que encontrará a continuación.
QuantEnt sits above existing identity, data, security, and workflow systems. It transforms fragmented enterprise permissions, roles, telemetry, and metadata into structured control objects that can be analyzed, governed, and acted upon. The goal is to help organizations answer difficult questions such as: what authority exists, what that authority means, what risk it carries, and whether a human or AI-driven action should safely proceed.
This is a rare opportunity to join at an early stage and help build a technically ambitious platform in a clean, greenfield environment. The team has the opportunity to make foundational decisions about architecture, data models, distributed computation, graph infrastructure, AI integration, and engineering culture from the beginning.
Role Description We are looking for a Backend Developer to help build the core server-side platform behind QuantEnt.
This is a hands-on engineering role for someone who enjoys solving difficult backend problems, designing reliable systems, and working with complex data models. You will help build the services, APIs, distributed processing layers, graph infrastructure, data pipelines, and internal platform components that power QuantEnt's entitlement governance, risk modeling, semantic control, and AI governance capabilities.
Our codebase is written entirely in Python. We use Ray for distributed computation and scalable analytical workflows, and Neo4j for graph-based modeling, relationship analysis, and reasoning across identity, access, resources, roles, entitlements, and risk.
Design, build, and maintain backend services in Python.
Design and implement graph-based models and queries using Neo4j.
Work with graph, relational, semantic, and quantitative data structures.
Translate complex mathematical, graph-based, and product concepts into reliable production software.
Collaborate with data science, product, integration, and customer-facing teams.
Design backend components that are testable, observable, secure, and scalable.
Improve performance, reliability, and maintainability across the platform.
Backend services for entitlement and access governance.
Distributed computation and data-processing pipelines using Python and Ray.
Neo4j-backed graph models for identity, access, resources, entitlements, roles, and risk.
Graph-based reasoning and semantic control systems.
AI governance infrastructure for controlling how humans and AI agents access, interpret, and act on enterprise data.
Several years of professional backend software development experience.
Strong proficiency in Python .
Experience building production backend systems, services, APIs, or data-processing platforms.
Strong understanding of software architecture, data structures, testing, and system design.
Experience working with distributed systems, asynchronous processing, task queues, data pipelines, or large-scale computation.
Ability to reason clearly about complex systems and turn abstract requirements into working software.
Strong debugging, troubleshooting, and performance-analysis skills.
Comfort working in an early-stage environment where requirements may evolve and engineering judgment matters.
Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or a related technical field, or equivalent professional experience.
Experience with Neo4j, Cypher, graph databases, knowledge graphs, or graph-based data modeling.
Experience with FastAPI, Pydantic, SQLAlchemy, PostgreSQL, or similar backend technologies.
Experience with distributed data processing, numerical computing, analytics platforms, or machine-learning infrastructure.
Experience with NumPy, pandas, Polars, SciPy, NetworkX, or related Python data libraries.
Familiarity with IAM, IGA, cybersecurity, identity systems, access control, data governance, or enterprise security.
Experience with cloud platforms, Kubernetes, Docker, CI/CD, observability, and secure deployment practices.
Prior startup or early-stage product engineering experience.
Ideal Profile The ideal candidate is a strong backend engineer who enjoys hard technical problems and wants to build core infrastructure from an early stage. You do not need to be an IAM expert, but you should be excited by complex systems, distributed computation, graph-based reasoning, mathematical modeling, AI-native infrastructure, and software that has to work reliably in enterprise environments.
It is an opportunity to help build the foundation of a technically ambitious platform with no inherited technical debt and significant room for original engineering decisions.
Work on a technically deep product at the intersection of backend engineering, distributed systems, graph intelligence, quantitative modeling, identity governance, data governance, and AI control.
Help shape the architecture of an early-stage platform from the beginning. xhfqzwm
Build entirely in Python, using Ray, Neo4j, and other modern technologies.
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