ClubSec

Pour un acteur de l'assurance ContexteEngineering_Software EngineeringMissions1.SSDLC Co-Definition &amp; Consolidation • Collaborate with security, development, and architecture teams to co-define the future SSDLC framework • Integrate AI-assisted coding tools and automated security practices into SSDLC phases • Establish guidelines and best practices for secure AI-augmented development • Define security controls and validation mechanisms for AI-generated code • Create documentation, playbooks, and training materials for SSDLC adoption <a target="_blank" rel="noopener noreferrer nofollow" href="http://2.AI">2.AI</a> &amp; Agentic Solutions Experimentation • Lead proof-of-concepts for AI coding assistants, code generation, and agentic workflows • Evaluate emerging AI tools and frameworks for software development use cases <a target="_blank" rel="noopener noreferrer nofollow" href="http://3.Design">3.Design</a> experiments to measure productivity gains, code quality impact, and security implications <a target="_blank" rel="noopener noreferrer nofollow" href="http://4.Build">4.Build</a> prototypes demonstrating AI integration across the development lifecycle (planning, coding, testing, deployment, maintenance) 5. Analyze data and present findings to stakeholders to drive adoption decisions 6.Contribute to the internal AI developer community and knowledge sharing 7.Internal Platform Support &amp; Evolution • Enhance the in-house AI code assistant with advanced features • Implement security guardrails to prevent sensitive data exposure or insecure code generation • Integrate solutions with developer IDEs and workflows for seamless adoption • Monitor usage patterns and gather feedback for continuous improvement • Evolve the security tools orchestration platform to incorporate AI-powered vulnerability detection • Automate security testing workflows and integrate with CI/CD pipelines • Improve tool orchestration, reporting, and remediation guidance • Develop features for automated code quality assessment and grading within the engineering excellence platform • Build dashboards and analytics for engineering metrics, create standardization frameworks, and integrate AI-powered insights for continuous improvementProfil recherchéExpertise: • Seniorexpertise in software engineering, with a focus on web application development. • Proven expertise with AI/ML technologies, preferably in software development contexts. • Proven expertise in building internal developer tools, platforms, or frameworks. • Expertise working in large, distributed organizations with multiple stakeholders. • Consulting, advisory, or cross-functional technical leadership roles. • Deep understanding of Secure SDLC methodologies and security testing practices. • Expertise implementing or working with AI coding assistants and code generation tools. • Expertise in security vulnerabilities (OWASP Top 10, CWE, CVE) and remediation strategies. • Familiarity with DevSecOps practices and security automation in CI/CD pipelines. • Understanding of LLMs, prompt engineering, and AI agent architectures. • Expertise with code quality metrics, static/dynamic analysis tools, and engineering excellence frameworks. Technical Expertise: • Expert in modern web development (JavaScript/TypeScript, Python, Node.js, React/Vue/Angular). • Proficient in multiple programming languages (Java, Go, C#, etc.). • Software architecture patterns and design principles; REST APIs, microservices, and cloud-native development. • Proven expertise with LLM APIs, AI agent frameworks, prompt engineering, and related technologies. • Proficiency with SAST/DAST tools, dependency scanning, secrets management, and secure coding practices. • Expertise with CI/CD pipelines, cloud platforms (AWS, Azure), containerization, Infrastructure as Code, and observability tools. • Familiarity with security frameworks (NIST, ISO 27001, OWASP SAMM) and developer productivity tools. Other Qualifications: • Visionary and problem-solving mindset; data-driven decision-making and risk assessment. • Effective communication of technical concepts to diverse audiences. • Strong stakeholder management, community building, and cross-functional collaboration. • Mentor and adapt leadership style to context and cult

AI Lead engineer (DevsecOps)

AI Lead engineer (DevsecOps)

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