The Secure AI Innovation Engineer is a hybrid security role combining Application Security, Cloud Security and AI Security, with a strong focus on innovation, automation and improving clients’ security maturity. The role supports organizations in designing and implementing modern, secure and scalable solutions and in safely adopting AI and Agentic AI technologies.
Your responsibilities:
- Assess clients’ security posture, identify gaps and define pragmatic improvement roadmaps across applications, cloud platforms and development processes.
- Act as a trusted security advisor and propose modern solutions that improve security, automation and operational efficiency.
- Design and implement end-to-end controls for applications, cloud infrastructure, development pipelines and operational environments.
- Enable secure adoption of LLM-based solutions and Agentic AI.
- Define security guardrails and mitigate AI-specific risks such as prompt injection, data leakage, data poisoning, model abuse, insecure integrations and misuse of autonomous agents.
- Embed security into SDLC and SSDLC in cooperation with development, architecture and platform teams.
- Improve CI/CD pipelines, Infrastructure-as-Code, APIs and cloud-native development environments.
- Perform application and system security assessments aligned with OWASP Top 10, OWASP ASVS and OWASP API Top 10.
- Conduct threat modelling for cloud-native, hybrid, distributed and AI-enabled architectures.
- Design and support secure architectures across Azure, AWS or GCP, including identity, network security, data protection and platform security.
- Secure containerized and cloud-native environments, including Kubernetes.
- Use automation and AI-powered tools to improve vulnerability detection, code and configuration analysis, threat detection and security operations.
- Translate complex security risks into clear recommendations for technical and non-technical stakeholders.
- Help clients build long-term security capabilities and securely modernize cloud foundations, data flows, model integrations, inference APIs and IAM.
Requirements:
- Background in IT, software development, cloud engineering or security.
- Understanding of end-to-end architectures, including monolithic, microservices, event-driven and cloud-native designs.
- Foundational knowledge of Application Security, OWASP standards, secure coding and common attack techniques such as XSS, SQL injection and CSRF.
- Basic to intermediate knowledge of cloud security, shared responsibility, IAM, network and data security.
- Familiarity with SSDLC, secure design, testing and vulnerability management.
- Interest in AI, LLMs and Agentic AI and awareness of their security challenges.
- Knowledge of at least one cloud platform: Azure, AWS or GCP.
- Familiarity with CI/CD, DevSecOps, REST APIs and API security.
- Scripting or programming skills in Python, Java, JavaScript, C#, Go or another language.
- Clear communication, ownership, curiosity and ability to work independently and with teams.
Nice to have:
- Experience in Application Security or Cloud Security.
- Knowledge of AI system architectures, data pipelines, model lifecycle and inference services.
- Exposure to Docker, Kubernetes, CNAPP, CSPM, SIEM/SOAR, cloud-native security tools or security automation.
- Cloud or security certifications.
What Accenture offers:
- Permanent employment contract.
- Individual support from a People Lead and a defined development path, including coaching.
- Soft, technical and language training, e-learning, GenAI training and co-financing of courses and certifications.
- Employee Assistance Program with legal, financial and psychological consultations.
- Employee share purchase plan and quarterly dividends for eligible employees.
- Paid referral program, private medical care and life insurance.
- Worksmile platform with services including the Multisport card.
Recruitment stages: online application, phone interview, optional online tests, optional technical skills check and interview with the future Team Leader.