Descrição da Vaga

AI SECURITY ARCHITECT (HYBRID LISBON)

Portuguese company hires for hybrid position

📍 Location: Lisbon, Portugal

⚠️ Only candidates already based in Portugal will be considered

💼 Work Model: Hybrid

🗣️ Language Requirements: Fluent Portuguese and English B2+/C1 — mandatory

🕓 Seniority: Senior (6+ years)

🏭 Sector: Cybersecurity

💲Rate Between €2400 - 2700 RV

⚠️ Instructions: Please send your CV in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success

About the Opportunity

You will support AI and GenAI initiatives throughout their lifecycle, from initial design to production deployment. Working closely with security, engineering, product, cloud, and data teams, you will assess architectures, identify risks, define security requirements, and verify that effective and auditable controls have been implemented.

The role requires a pragmatic security mindset, the ability to challenge technical decisions, and the capacity to translate emerging AI risks into clear, enforceable requirements.

Key Responsibilities

• Support and review AI and GenAI use cases from the design phase through production.
• Define security requirements for AI platforms, APIs, agents, tool usage, and third-party integrations.
• Conduct architecture reviews, threat modelling, and security assessments of AI solutions.
• Validate integrations and deployments against security, privacy, logging, monitoring, and auditability requirements.
• Identify, assess, and mitigate AI-specific risks, including:
• Prompt injection and jailbreak attacks
• Sensitive information disclosure and data leakage
• Unsafe tool usage and excessive agent autonomy
• Abusive or unbounded resource consumption
• Insecure integrations and poisoned inputs
• Define data-usage guardrails for personal, confidential, sensitive, or regulated information.
• Ensure the implementation of secure logging, monitoring, audit trails, and evidence of control effectiveness.
• Contribute to AI security governance, standards, policies, and secure-by-design patterns.
• Collaborate with technical teams to ensure that security controls are correctly and effectively applied.

Mandatory Requirements

• 6+ years of professional experience in cybersecurity.
• Background in application security, product security, cloud security, or security architecture.
• Understanding of GenAI and LLM-based solutions from a security and risk perspective.
• Practical experience conducting security reviews, architecture reviews, and threat-modelling exercises.
• Experience defining, implementing, or validating technical security controls.
• Strong knowledge of IAM, API security, secrets management, logging, monitoring, and control validation.
• Knowledge of data protection, privacy, data minimisation, and secure handling of sensitive or regulated information.
• Ability to challenge technical implementations and verify whether security controls have been applied effectively.
• Fluent Portuguese and English at B2+/C1 level.

Preferred Experience

• Familiarity with AWS and/or Microsoft Azure in the context of AI workload security.
• Exposure to AWS Bedrock, Azure OpenAI, Azure AI Foundry, or similar GenAI platforms.
• Understanding of:
• Guardrails and content controls
• IAM and least-privilege principles
• Logging, observability, and auditability
• Sensitive-data handling and data protection
• Familiarity with Databricks from a security-review perspective, including:
• Access controls and data permissions
• Workspaces, jobs, pipelines, and notebooks
• Secrets management and networking
• Data governance
• Knowledge of the OWASP Top 10 for LLM Applications and Agentic AI.
• Familiarity with SAIF — Secure AI Framework.
• Understanding of Model Context Protocol (MCP) and agent-to-tool security.
• Knowledge of Agent-to-Agent (A2A) architectures and agentic trust boundaries.
• Awareness of emerging AI risk taxonomies, such as MCP-38.
• Exposure to DevSecOps and/or MLOps environments.

The Ideal Candidate

The ideal candidate is an experienced cybersecurity professional who understands how traditional security principles must evolve when applied to AI, GenAI, and agentic solutions. You can identify emerging threats, translate risks into actionable technical requirements, and verify that security controls are practical, effective, and auditable.

You are confident working across security, product, engineering, cloud, and data teams. You combine strong technical judgment with clear communication, risk prioritisation, and a pragmatic approach to secure AI adoption.

Questions for Candidates

• Do you have at least six years of professional experience in cybersecurity?
• What experience do you have in application security, product security, cloud security, or security architecture?
• Have you conducted architecture reviews, security assessments, or threat-modelling exercises for AI or GenAI solutions?
• Have you assessed risks such as prompt injection, jailbreaks, data leakage, unsafe tool usage, or excessive agent autonomy?
• What experience do you have with IAM, API security, secrets management, logging, monitoring, and auditability?
• Have you worked with AWS Bedrock, Azure OpenAI, Azure AI Foundry, or other GenAI platforms?
• Have you reviewed Databricks environments from a security perspective?
• Are you familiar with OWASP guidance for LLM applications, SAIF, MCP, A2A architectures, or agentic trust boundaries?
• Have you worked in DevSecOps or MLOps collaboration environments?
• Can you communicate professionally in English at B2+/C1 level and fluently in Portuguese?
• Where are you currently based?
• What is your availability to start?
• What are your salary or daily-rate expectations?

Keywords to Include in Your CV

AI Security, Generative AI Security, GenAI, LLM Security, AI Security Architecture, Cybersecurity, Security Architecture, Application Security, Product Security, Cloud Security, Architecture Review, Security Review, Threat Modelling, Prompt Injection, Jailbreaks, Data Leakage, Sensitive Data, AI Guardrails, Agentic AI, AI Agents, Tool Security, IAM, Least Privilege, API Security, Secrets Management, Logging, Monitoring, Observability, Auditability, Control Validation, Data Protection, Data Privacy, Data Minimisation, Secure by Design, AI Governance, AWS, Microsoft Azure, AWS Bedrock, Azure OpenAI, Azure AI Foundry, Databricks, OWASP Top 10 for LLM Applications, OWASP Agentic AI, SAIF, Model Context Protocol, MCP, Agent-to-Agent, A2A, Agentic Trust Boundaries, MCP-38, DevSecOps, MLOps, Risk Assessment, Security Controls

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