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 security maturity uplift. This role supports clients in evolving their cybersecurity capabilities, designing and implementing modern, secure, and scalable solutions, and enabling safe adoption of AI and Agentic AI technologies. The engineer acts as a trusted security advisor, helping organizations securely modernize their environments, processes, and teams. The role does require deep values broad technical foundations, curiosity, ownership, and growth mindset, with the ability to connect security, cloud, applications, and AI into cohesive, end‑to‑end solutions.
THE WORK:
- 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.
Flexible: The work location for this role may include a mix of working remotely, onsite at a client or in an Accenture office - depending on specific project circumstances.
With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.