Python Developer

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.

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.

We are building our primary — and only — development center in Madrid, and we are now expanding the engineering team.

This is a rare opportunity to join at an early stage and help build a technically ambitious platform in a clean, greenfield environment. There is no legacy architecture to unwind and no inherited technical debt. 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.

This role is a strong fit for someone who wants to do more than maintain existing systems. We are still early, which means you will help shape core architecture, engineering practices, system design, and product foundations from the beginning.

Responsibilities

Design, build, and maintain backend services in Python.

Build distributed processing workflows using Ray and related technologies.

Design and implement graph-based models and queries using Neo4j.

Develop APIs, services, and internal platform components for QuantEnt’s core product.

Build systems that ingest, normalize, transform, and analyze enterprise identity, entitlement, role, risk, and metadata signals.

Work with graph, relational, semantic, and quantitative data structures.

Help build AI-native infrastructure that supports semantic interpretation, risk-aware decisioning, and governed human or AI-driven action.

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.

Contribute to foundational architectural decisions in a clean-slate engineering environment.

Help establish engineering standards, development workflows, and technical best practices.

What You Will Work On

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.

Risk and exposure calculation infrastructure.

Graph-based reasoning and semantic control systems.

AI governance infrastructure for controlling how humans and AI agents access, interpret, and act on enterprise data.

APIs for customer integrations and internal platform workflows.

Systems for certification, drift detection, role intelligence, and governance automation.

Infrastructure that supports safe, explainable, and risk-aware decision-making in enterprise environments.

Required Qualifications

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.

Good communication skills and ability to collaborate across technical disciplines.

Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or a related technical field, or equivalent professional experience.

Preferred Qualifications

Experience with Ray or similar distributed-computing frameworks.

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 AI systems, LLM infrastructure, agentic AI workflows, retrieval systems, semantic models, or AI governance.

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.

Strong background or interest in mathematics, statistics, algorithms, graph theory, optimization, or quantitative modeling.

Experience building systems for regulated enterprise environments.

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.

We are especially interested in engineers who are rigorous, curious, practical, and comfortable thinking from first principles. This is not a narrow feature-development role. 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.

Why Join QuantEnt

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.

Build entirely in Python, using Ray, Neo4j, and other modern technologies.

Join a clean, greenfield engineering environment with no legacy architecture to unwind.

Help define engineering culture, standards, and technical direction in Madrid.

Solve problems that matter to large, complex, regulated enterprises.

Work with a team that values rigorous thinking, practical engineering, and strong technical judgment.