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

Accenture is hiring a Secure AI Innovation Engineer, a hybrid role combining Application Security, Cloud Security, and AI Security. The role focuses on innovation, automation, and security maturity uplift for clients by designing and implementing secure, scalable solutions and advising on safe AI adoption.

• Strong interest in cybersecurity, innovation, and modern technologies with a growth mindset.
• Background in IT, software development, cloud engineering, or security with foundational knowledge of 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, ASVS, secure coding principles, and common attacks.
• Basic to intermediate understanding of Cloud Security concepts including shared responsibility, IAM, network and data security.
• Familiarity with SSDLC principles including security requirements, 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 and collaboratively.
• Basic experience or knowledge of one major cloud platform (Azure, AWS, or GCP), CI/CD pipelines, DevSecOps, REST APIs, and API security.
• Scripting or programming skills in at least one language such as Python, Java, JavaScript, C#, or Go.

Nice to have:

• 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 related to cloud or security (not required).
• Exposure to container platforms (Docker, Kubernetes), CNAPP, CSPM, SIEM/SOAR, cloud-native security tooling, automation, and orchestration.

• Support clients in increasing cybersecurity maturity by assessing security posture and defining improvement roadmaps.
• Act as a trusted security advisor proposing modern and innovative security solutions.
• Design and implement end-to-end security controls for applications, cloud infrastructure, and operational environments.
• Enable secure adoption of AI technologies, including LLM-based solutions and Agentic AI.
• Define and implement security guardrails for AI environments addressing AI-specific security risks.
• Collaborate with development, architecture, and platform teams to embed security into SDLC and SSDLC.
• Support and improve secure development environments including CI/CD pipelines and Infrastructure-as-Code.
• Perform application and system security assessments aligned with OWASP standards.
• Conduct or facilitate threat modeling for end-to-end solutions including AI-enabled architectures.
• Design and support secure cloud and hybrid architectures across Azure, AWS, or GCP.
• Support containerized and cloud-native environments ensuring secure configuration and posture management.
• Leverage automation and AI-powered security tools to improve detection and security operations efficiency.
• Translate complex security risks into actionable recommendations for technical and non-technical stakeholders.
• Support clients in building long-term security capabilities for secure digital transformation and responsible AI use.
• Secure cloud foundations, data flows and pipelines, AI model integration and inference APIs, Identity and Access Management.

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