Technical Engineering Lead (Portugal)

About the role

Technical Engineering Lead (Portugal)

Location- Lisbon, Portugal

ABOUT THE ROLE:

As Technical Engineering Lead, you will provide hands-on technical leadership for the Portugal-based R&D team and help establish the technical foundation for HiddenLayer’s Governance, Risk, and Compliance module. Your initial focus will be the GRC engine, a foundational platform capability that represents regulatory obligations as maintainable, machine-executable policy engines and guides customers through risk classification and conformity assessment.

This is a senior, high-ownership role for an engineer who can move between architecture, implementation, and technical direction. You will design the compliance rules engine, translate complex regulatory requirements into practical software models, build reliable cloud services, and set engineering standards that enable the team to scale. You will also mentor future hires and partner with product, security, and governance stakeholders to deliver a defensible, usable compliance experience.

WHO WE ARE:

HiddenLayer protects the world’s most valuable technologies from adversarial AI attacks. We were founded by AI professionals and security specialists with first-hand experience of how insidious adversarial AI attacks can be to detect and defend against. Determined to prove that these attacks were preventable, the team developed a unique, patent-pending, productized solution to support organizations in accelerating their adoption of AI securely.

Our dedication to innovation has been recognized by prestigious awards such as RSA's Innovation Sandbox Winner, CB Insights AI 100, CyberTech 100, and SC's Most Promising Early-Stage Start-up.

WHAT YOU’LL DO:

- Define the architecture for the EU AI Act Compliance Engine within HiddenLayer’s GRC module, including service boundaries, data models, APIs, workflow orchestration, and integration points.

- Design a regulation-as-data approach that represents EU AI Act obligations in a versioned, testable, explainable, and maintainable rules engine.

- Build automated obligation and risk-tier mapping for registered AI systems, including classifications such as prohibited, high-risk, limited-risk, and minimal-risk use cases.

- Create conformity-assessment workflows that guide governance teams through the obligations and evidence applicable to each AI system.

- Develop secure, reliable, observable cloud-native services using Python and appropriate supporting technologies.

- Establish engineering practices for testing, CI/CD, code review, documentation, observability, incident readiness, and secure SDLC execution.

- Validate the rules engine and risk-tiering logic against representative AI systems and real-world regulatory scenarios, improving accuracy and explainability over time.

- Partner with product, security, legal, governance, and engineering stakeholders to convert regulatory and customer needs into clear technical deliverables.