ABOUT WELVAART
On a daily basis, we assume commitments and present solutions to our stakeholders in order to create a structure of human values, based on professionalism, honesty and rigor.
With a management based on Human Centered Design, we take care of our professionals with consistent career plans, but flexible with their needs and expectations of evolution. Our management team guarantees an empathetic and present leadership that will provide superior technological engagement and delivery to our clients' projects and products.
Project Scope
Ensure AI and GenAI solutions are designed and implemented securely, embedding security, privacy, and governance requirements throughout the lifecycle.
Responsibilities
- Review and support AI/GenAI use cases from design through to production.
- Define security requirements for AI platforms, APIs, agents, tools, and integrations.
- Conduct architecture reviews, security assessments, and threat modelling activities.
- Validate deployments and integrations against security, privacy, logging, and auditability requirements.
- Identify and mitigate risks such as:
- Prompt injection and jailbreaks
- Data leakage and sensitive information exposure
- Unsafe tool usage and excessive agent autonomy
- Uncontrolled AI consumption
- Insecure integrations and untrusted inputs
- Define guardrails for the secure use of sensitive, confidential, personal, and regulated data.
- Ensure effective logging, monitoring, audit trails, and security control validation.
- Contribute to AI security standards, governance frameworks, and secure-by-design practices.
- Collaborate with Architecture, Engineering, DevSecOps, and MLOps teams to strengthen AI security.
Requirements
- Experience in Cybersecurity, preferably in Application Security, Product Security, Cloud Security, or Security Architecture.
- Strong understanding of GenAI and LLM security risks and controls.
- Experience conducting security reviews, architecture reviews, and threat modelling exercises.
- Knowledge of IAM, API Security, Secrets Management, Logging, Monitoring, and security controls.
- Understanding of data protection, privacy, and secure handling of sensitive or regulated data.
- Ability to assess technical solutions and validate security control effectiveness.
- Strong communication, stakeholder management, and analytical skills.
Preferred Qualifications
- Experience with AWS and/or Azure AI environments.
- Experience with AWS Bedrock, Azure OpenAI, Azure AI Foundry, or similar GenAI platforms.
- Knowledge of:
- Guardrails and content controls
- Least privilege and IAM best practices
- Logging, observability, and auditability
- Data protection and sensitive data management
- Familiarity with Databricks security, including access controls, workspaces, jobs, pipelines, notebooks, secrets management, networking, and data governance.
- Familiarity with:
- OWASP Top 10 for LLM Applications / Agentic AI
- Secure AI Framework (SAIF)
- Model Context Protocol (MCP)
- Agent-to-Agent (A2A) architectures and trust boundaries
- MCP-38 and related emerging AI security frameworks
- DevSecOps and/or MLOps practices
What you can discover with us?
- Be part of a tech start-up
- Different scopes of project in different sectors
- Structure of fairness and equity salary (Consultant Profile)
- Training & Certification
- Career Path management
- More than 30 Partnerships
- Welvaart Ambassador Program
UNLEASH THE POWER OF YOUR CAREER