ProfileAmbitious people with a passion for this area;
Degree in Computer Engineering, Electrical Engineering or similar;
Background in Cybersecurity, ideally application security, product security, cloud security, or security architecture;
Understanding of Gen AI/LLM-based solutions from a security and risk perspective;
Experience with security reviews, architecture reviews, threat modelling, and defining technical controls;
Experience with IAM, API security, secrets management, logging, monitoring, and control validation;
Knowledge of data protection, privacy, data minimization, and secure handling of sensitive or regulated data;
Ability to challenge technical implementations and validate that controls are effectively applied;
Familiarity with AWS and/or Azure environments in the context of AI workload security;
Exposure to AWS Bedrock, Azure Open AI/Azure AI Foundry, or similar Gen AI platforms;
Familiarity with OWASP Top 10 for LLM Applications/Agentic AI, SAIF (Secure AI Framework), Model Context Protocol (MCP) and agent-to-tool security considerations, Agent-to-Agent (A2 A) architectures and agentic trust boundaries, and emerging risk taxonomies such as MCP-38;
Exposure to Dev Sec Ops and/or MLOps as a collaboration context;
Written and verbal communication skills (Portuguese and English);
Ability to work effectively and manage deadlines;
Sense of responsibility, commitment and integrity;
Focus on innovation, dynamism, autonomy and teamwork.
ResponsibilitiesSupport and review AI/Gen AI use cases from design through production;
Define security requirements for AI platforms, APIs, agents, tool use, and integrations;
Perform architecture reviews, threat modelling, and security reviews of AI solutions;
Validate integrations and deployments against security, privacy, logging, and auditability requirements;
Identify and mitigate risks such as prompt injection/jailbreaks, sensitive information disclosure/data leakage, unsafe tool use/excessive agency, abusive or unbounded consumption, insecure integrations or poisoned inputs;
Define guardrails for data usage, especially for sensitive, personal, confidential, or regulated data;
Ensure secure logging, monitoring, audit trails, and evidence of control effectiveness;
Contribute to AI security governance, standards, and secure-by-design patterns.
What can you expect?Hybrid working model;
National and international projects;
Health Insurance Benefit for all employees;
A fair system of competitive rewards upon knowledge and experience;
Certification, technical and behavioral training to become the best version of yourself;
Team Building and Happy Hours;
Committed and successful teams;
Opportunity to work in a challenging environment with dynamic teams and innovative projects;
Promotion of happiness, well-being at work and physical and emotional health, with initiatives that allow a work-life balance culture;
Benefit scheme along with partners.
In line with our diversity, equity, and inclusion policy, at ITSector we value the creation of a work environment where every employee is treated with dignity and where every opinion matters. We believe that diversity makes us stronger and contributes to the innovation and success of our teams.
In ITSector there is no room for any potential bias, from the Talent Acquisition process till the Career & Development of our employees, diversity and inclusion, regardless of age, gender, ethnicity, race, nationality or any form of discrimination incompatible with dignity of human rights are our key drivers.