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HiddenLayer

AI security platform for agentic apps

Technical Engineering Lead

Backend EngineeringConfirmed live in the last 24 hours
Full-timeLisbon, PortugalNo salary listed

About the Job

Requirements

  • At least 8 years of experience delivering production systems and making architecture decisions across complex technical domains.
  • Experience engineering in Python and Golang, with strong foundations in cloud architecture, distributed systems, APIs, data modeling, and secure software development.
  • Ability to translate complex, evolving requirements into clear technical models, maintainable rules, and reliable workflows.
  • Interest in AI, cybersecurity, governance, risk, and regulation, with the judgment to distinguish policy intent from implementation detail.
  • Ability to write production code, review designs, troubleshoot difficult problems, and raise engineering quality through example.
  • Ability to document decisions, surface tradeoffs early, and build alignment across engineering, product, security, and governance teams.
  • Based in Lisbon.
  • Professional fluency in English.

Responsibilities

  • Define architecture for the EU AI Act Compliance Engine within the GRC module, including service boundaries, data models, APIs, workflow orchestration, and integration points.
  • Design a regulation-as-data approach representing 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 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 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.
  • Make pragmatic architecture decisions in an evolving product environment, balancing correctness, extensibility, delivery speed, and operational risk.
  • Provide technical leadership and mentorship for subsequent hires, helping build a strong engineering culture and a scalable Portugal R&D function.

Desired Qualifications

  • Experience building compliance, governance, risk, audit, policy, workflow, or other rules-driven enterprise software.
  • Working knowledge of the EU AI Act, AI governance, model risk management, conformity assessment, or related regulatory frameworks.
  • Experience developing or operating machine-learning platforms, MLOps systems, AI infrastructure, or software adjacent to AI workflows.
  • Experience building security products, cloud security tooling, GRC platforms, or integrations across security and enterprise ecosystems.
  • Experience with AWS or Azure and containerized workloads using Docker and Kubernetes.
  • Familiarity with event-driven systems, workflow engines, policy-as-code, API gateways, service-oriented architectures, or distributed systems.
  • Experience with infrastructure as code, such as Terraform, Pulumi, CloudFormation, or Bicep.
  • Familiarity with observability practices and tools for metrics, logs, traces, service health, and operational diagnostics.
  • A master’s degree or equivalent advanced training in computer science, software engineering, artificial intelligence, cybersecurity, or a related discipline.

About the Company

HiddenLayer

AI security platform for agentic apps

HiddenLayer is an Austin-based AI security company that protects agentic, generative and predictive AI applications across discovery, supply-chain scanning, attack simulation and runtime protection, without requiring customers to hand over model weights or training data. Its products defend against prompt injection, agent manipulation and malicious tool use, covering the full lifecycle from discovery to runtime. The company distinguishes itself by offering defense without needing access to weights or data and by focusing on agentic security capabilities such as runtime protection and harness security for frontier models, with a track record of enterprise customers and patents. Its goal is to secure AI systems at scale—across discovery, supply chain, simulation and runtime—while expanding enterprise reach globally, including EMEA, and continuing development of agentic security capabilities.

Company size
51-200
Company stage
Series B
Total funding
$156M
Headquarters
Austin, TX
Founded
2022

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