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# Lead Software Engineer

- **Company:** Cboe Global Markets
- **Location:** Amsterdam, Netherlands
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Software Quality, Data Structures, Monitoring of Systems, Python (Programming Language), Log Analysis, Software Architecture, Software Engineering, Strategies of Testing, System Availability, Technical Debt, Numerical Computing, Backend, Software Coding, Code Restructuring, Data Pipelines
- **Published:** October 19, 2026
- **Apply:** https://www.adzuna.nl/details/5819883251

## About the Role

* 1 Backend Engineer (Java/Python, platform & integration focus)
 * 1 Quant Engineer / Product Owner (Python, quantitative and model-heavy logic), Core Technical Skills
 * Strong experience designing and owning complex backend systems in Java, with Python exposure in the past being a strong plus.
 * Proven track record with data-heavy, computation-intensive platforms.
 * Solid understanding of software architecture, testing strategies, and system observability.
 * Experience operating in regulated or high-risk environments is a strong advantage.

AI-Assisted Engineering

 * Demonstrated, hands-on experience using AI tools as part of the daily engineering workflow.
 * Ability to critically evaluate AI-generated output and integrate it safely into production-grade systems.
 * Strong interest in continuously improving engineering effectiveness through tooling and automation.

Data & Quant Background

 * Strong foundation in data structures, numerical computing, and analytical problem-solving.
 * Ability to reason about quantitative models without necessarily being the primary model author.
 * Experience collaborating with quants or risk model developers is highly desirable.

Soft Skills

 * Clear, structured communicator with strong written and verbal skills.
 * Comfortable leading technical discussions and challenging ideas constructively.
 * Pragmatic, calm, and accountable in high-pressure environments.
 * Strong sense of ownership and intrinsic motivation.

## Description

The Tech Lead is expected to work hands-on across the stack, while clearly delineating responsibilities between platform engineering concerns and quantitative model implementation.

Technical Ownership & Architecture

 * Act as technical owner of the Clearisq codebase within CCEU.
 * Define and maintain the target architecture, including boundaries between:
 + Quantitative models
 + Data pipelines and analytics
 + Platform services and integrations
 * Drive architectural decision records (ADRs) and align with CCEU architecture governance.
 * Balance pragmatic delivery with long-term maintainability in a safety-critical CCP context.

Code Quality, Reliability & Risk Awareness

 * Set and enforce engineering standards for correctness, performance, testing, and observability.
 * Ensure the platform meets high availability, determinism, and auditability expectations typical for CCP risk systems.
 * Own the technical approach to numerical correctness, reproducibility, and explainability of calculations.
 * Proactively manage technical debt, lifecycle concerns, and vendor-originated legacy code.

AI-Assisted Software Engineering

 * Act as a role model and multiplier for AI-assisted engineering practices within the team - and the wider software engineering department.
 * Leverage AI tools for:
 + Code comprehension of a complex acquired codebase
 + Code development for changes
 + Refactoring and modernization
 + Test generation and validation scenarios
 + Log analysis, performance investigation, and incident learning
in line with CCEU and Cboe-wide AI adoption initiatives.

 * Establish guardrails to ensure AI usage enhances quality, security, and correctness rather than eroding them.

Data & Quantitative Awareness

 * Possess deep understanding of data-intensive systems, including:
 + Large in-memory datasets
 + Time-series and historical simulations
 + Performance-sensitive numerical computation
 * Collaborate closely with the Quant Engineer to:
 + Translate risk methodology into robust software constructs
 + Challenge assumptions where model design meets system constraints
 * Ensure clean separation between model logic and platform mechanics.

Stakeholder Collaboration & Soft Skills

 * Serve as the technical interface between Software Engineering, Risk, Quant, Operations, and external stakeholders.
 * Communicate complex technical trade-offs clearly to non-engineers.
 * Actively surface risks, constraints, and dependencies early.
 * Contribute to cross-team alignment in a multi-domain clearing platform.