Secure AI Innovation Engineer (regular/senior) (She/He/They)

Technologies we use

Your responsibilities

• Support clients in increasing their cybersecurity maturity by assessing current security posture, identifying gaps, and defining pragmatic improvement roadmaps across applications, cloud platforms, and development processes.
• Act as a trusted security advisor, proposing modern and innovative security solutions that improve security posture, enable automation, increase operational efficiency, and enhance the effectiveness and quality of security teams.
• Design and implement end‑to‑end security controls covering applications, cloud infrastructure, development pipelines, and operational environments.
• Enable secure adoption of AI technologies, including LLM‑based solutions and Agentic AI, by designing and securing client environments to support safe and responsible AI usage.
• Define and implement security guardrails for AI environments, including: identify, assess, and mitigate AI‑specific security risks, such as prompt injection, data leakage, data poisoning, model abuse, insecure integrations, and misuse of autonomous AI agents.
• Collaborate with development, architecture, and platform teams to embed security into SDLC and SSDLC, following security‑by‑design and shift‑left principles.
• Support and improve secure development environments, including CI/CD pipelines, Infrastructure‑as‑Code, APIs, and cloud‑native platforms.
• Perform or support application and system security assessments, aligned with industry standards such as OWASP Top 10, OWASP ASVS, and OWASP API Top 10.
• Conduct or facilitate threat modeling for end‑to‑end solutions, including cloud‑native, hybrid, distributed, and AI‑enabled architectures.
• Design and support secure cloud and hybrid architectures across Azure, AWS, or GCP, covering identity, network security, data protection, and platform security.
• Support containerized and cloud‑native environments (e.g. Kubernetes‑based platforms) by ensuring secure configuration, posture management, and workload protection.
• Leverage automation and AI‑powered security tools to improve vulnerability detection, code and configuration analysis, threat detection, and security operations efficiency.
• Translate complex security risks into clear, actionable recommendations for technical and non‑technical stakeholders.
• Support clients in building long‑term security capabilities, enabling secure digital transformation and responsible use of AI technologies.
• Secure cloud foundations, data flows and pipelines, AI model integration and inference APIs, Identity and Access Management.

Our requirements

• Strong interest in cybersecurity, innovation, and modern technologies, with a clear willingness to learn, grow, and take ownership of security topics.
• Background in IT, software development, cloud engineering, or security, with foundational knowledge across applications and infrastructure.
• Understanding of end‑to‑end system architectures, including monolithic, microservices, event‑driven, and cloud‑native designs.
• Foundational knowledge of Application Security, including: OWASP Top 10 / OWASP ASVS, secure coding principles and common attack techniques (e.g. XSS, SQLi, CSRF).
• Basic to intermediate understanding of Cloud Security concepts, including: cloud shared responsibility model, Identity and Access Management, network and data security in cloud environments.
• Familiarity with SSDLC principles, including security requirements, secure design, testing, and vulnerability management.
• Interest in AI, LLMs, and Agentic AI, with awareness of associated security challenges.
• Ability to communicate clearly with both technical and non‑technical stakeholders.
• Ownership mindset, curiosity, and ability to work independently while collaborating with teams.
• Basic experience or knowledge of: one major cloud platform (Azure, AWS, or GCP), CI/CD pipelines and DevSecOps concepts, REST APIs and API security fundamentals.
• Scripting or programming skills in at least one language (e.g. Python, Java, JavaScript, C#, Go).

Optional

• Experience in Application Security or Cloud Security roles.
• Understanding of AI system architectures, including data pipelines, model lifecycle, and inference services.
• Experience or curiosity around AI‑driven security tools and automation.
• Industry certifications (cloud or security) are a plus but not required.
• Exposure to: Container platforms (Docker, Kubernetes), CNAPP, CSPM, SIEM/SOAR, or cloud‑native security tooling, security automation and orchestration.

What we offer

• Permanent employment contract.
• Individual support of a People Lead and a specific path of professional development, as well as the possibility of a session with a Coach.
• A wide training package (soft, technical, and language training offer, access to the e-learning platforms, Gallup test, GenAI training, possibility of co-financing courses, and certification).
• Employee Assistance Program - legal, financial, and psychological consultations.
• Accenture employees eligible for the Employee share purchase plan automatically become eligible for quarterly dividends if they own company shares.
• Paid employee referral program.
• Private medical care, life insurance.
• Access to the Worksmile platform (possibility of using a wide range of products and services, including the Multisport card).