Senior Security Engineer (AI/Cloud)

Support the Enhesa’s cybersecurity infrastructure by implementing robust security controls, deploying innovative security solutions, and investigating security incidents. This role is central to Enhesa’s application and cloud security posture, with growing exposure to securing AI/ML systems and generative AI tools as adoption expands across the organization. This role is pivotal in maintaining the security posture through meticulous incident analysis and effective mitigation strategies. Beyond technical responsibilities, the position requires excellent collaboration and communication with various departments to align security policies and procedures with overall business objectives and compliance regulations. The role works closely with Application Engineering and Cloud Platform teams, and increasingly with AI teams, to embed security throughout the software development lifecycle and cloud infrastructure environments. The successful candidate will provide guidance on secure design patterns, conduct comprehensive security reviews of application code and cloud architectures, and, as AI adoption grows, contribute to securing AI-powered features and managed AI services.

Responsibilities

Secure the SDLC and Cloud Infrastructure: Conduct security reviews of application code and cloud architectures (AWS, Azure, GCP), and integrate security controls, automated testing, and vulnerability management into CI/CD pipelines and DevSecOps workflows; Partner with Engineering Teams: Act as a hands-on security partner to Application Engineering and Cloud Platform teams, reviewing designs and providing guidance on secure design patterns throughout the development lifecycle; Champion Security Culture: Collaborate with Tech Leads and the Security Champions network to share secure coding practices, run awareness sessions, and raise the security bar across engineering teams; Contribute to AI Security Practices: Support security reviews of AI/ML systems and pipelines as they are introduced, helping assess risks such as prompt injection, data poisoning, and model supply chain vulnerabilities (OWASP LLM Top 10), and grow this expertise over time; Investigate Security Incidents: Lead investigation, mitigation, and recovery efforts for security incidents, including those affecting cloud infrastructure and, as relevant, AI/ML services and inference endpoints; Monitor Emerging Threats: Track emerging cybersecurity trends and vulnerabilities — including in the AI/ML space — and help evolve Enhesa’s security controls to address new risks

Requirements

Bachelor’s or advanced degree in computer science, artificial intelligence, mathematics, or related field or professional cybersecurity certifications in lieu of a formal degree; At least 5 years of experience as a cybersecurity professional, with a strong background in application security and/or cloud security; Application Security (AppSec) and Secure Software Development Lifecycle (SSDLC): familiarity with integrating security practices into CI/CD pipelines, code review processes, DevSecOps and MLSecOps workflows; OWASP Top 10: solid understanding of common web application vulnerabilities; Knowledge of networks (TCP/IP, LAN/WAN): solid understanding of networking basics, including TCP/IP protocols, configuration and operation of Local Area Networks (LAN) and Wide Area Networks (WAN); Basic familiarity with the OSI model, including its seven layers and how they contribute to network communications and cybersecurity practices; Security protocols (HTTPS, DNS, SMTP, FTP, SSH); Firewalls (IDS/IPS): familiarity with the concepts and purposes of these tools; Understanding of information security principles such as confidentiality, integrity, and availability; Familiarity with operating systems, especially Windows, Linux or Unix, and MacOS; Knowledge and familiarity with incident investigation and response processes; Programming languages (Python, PowerShell); familiarity with API security testing and secure coding practices in web application stacks; Knowledge of securing cloud environments (AWS, Azure, GCP); Familiarity with concepts like IAM (Identity and Access Management), encryption in transit and at rest, and shared responsibility models; Understanding of securing virtual machines and containerized environments; Fluency in English; Creativity, dynamics, and ability to work independently yet transparently towards colleagues; Strong teamwork skills with colleagues and external partners; Individual and team problem-solving skills

Nice to have

Hands-on exposure to AI/ML security, LLM security, or securing AI-driven systems; Familiarity with the OWASP LLM Top 10 (e.g. prompt injection, insecure output handling, model supply chain risks); Exposure to threat vectors specific to AI systems, such as adversarial attacks, data poisoning, model inversion, or securing inference endpoints; Exposure to securing AI/ML workloads and managed AI services (e.g. Azure OpenAI, AWS Bedrock, GCP Vertex AI); Relevant security certifications (e.g. CISSP, CEH, CCSP, OSCP); Any additional language skills

Benefits

Competitive salary package & benefits; Flexible home-working policy; Work/life balance; Fast-paced and driven environment; Accountability and pride for your projects; Sponsorship and support for obtaining an AI security certification (e.g. AAISM or CompTIA SecAI+)