AI Expert – DevSecOps
Il y a 2 jours
Paris, Île-de-France
Keoni
Temps plein
Gratuit avec email ou Google
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AI Expert – DevSecOps Context: The role requires expertise in artificial intelligence, particularly agentic AI: LLM, agents, MCP, skills, RAG, prompting, and code generation, within the team.
Êtes-vous le/la candidat(e) idéal(e) pour cette opportunité ? Assurez-vous de lire la description complète ci-dessous.
The team explores, prototypes, and tools AI applications with a dual objective:
• To leverage AI for the continuous integration pipeline and tooling, primarily GitLab;
• To broadly familiarize the team with these technologies.
The ideal candidate is technically skilled but also capable of understanding business challenges and communicating effectively with non-technical stakeholders.
MISSIONS
• Creation of spikes and POCs around agentic AI: LLM, agents, RAGs, MCPs, prompting, code generation;
• Integration of AI into the CI/CD pipeline and DevSecOps tooling: GitLab, GitLab Duo and DAP in particular, MCPs on the pipeline tools ;
• Design of AI enablers and tools reusable by the train teams;
• Implementation and evaluation of the group's AI building blocks: Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• Design of AI agents and assistants applied to development and DevOps;
• Implementation of RAGs and use of knowledge bases;
• Technological monitoring and evaluation of AI solutions relevant to the train;
• Consideration of security and compliance issues in the use of AI – DevSecOps;
• Development of necessary components: scripts, integrations, APIs;
• Acculturation and dissemination within the train network: training, demonstrations, workshops;
• Writing and popularizing associated documentation in Confluence, for technical and non-technical audiences;
• Supporting train teams in adopting AI usage;
• Contributing to knowledge sharing and collective skills development.
Essential Technical Skills – Mandatory Requirements
• Mastery of agentic AI concepts: LLM, agents, MCP, RAG, prompting;
• Ability to design and integrate AI solutions: agents, RAG, model API calls;
• Strong fundamentals in AI-assisted development and code generation;
• Understanding of the link between AI, CI/CD, and DevSecOps tools, particularly GitLab;
• Ability to understand business challenges and communicate them clearly to non-technical audiences;
• Proficiency in REST APIs and AI service integration;
• Knowledge of the group's AI offerings: Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• Skills in evaluating AI solutions: relevance, robustness, and performance measurement;
• Knowledge of AI assistants for development: GitLab Duo, GitLab DAP;
• Awareness of security and compliance issues related to AI – DevSecOps.
Other key technical
skills:
• Development, particularly Python, and scripting;
• General IT technical knowledge: APIs, architecture, with an operational perspective;
• Knowledge of AWS and GCP clouds;
• Understanding of containerization and execution environments: Docker, Kubernetes/OpenShift;
• Knowledge of Confluence and Jira;
• Experience with agile methodologies (Scrum, SAFe) and teamwork;
• Proficiency in Microsoft Office Suite, Outlook, and Teams;
• Ability to explain complex concepts clearly and facilitate workshops;
• Understanding of how a DevSecOps platform works.
Technological Environment: A good understanding of the following ecosystem is expected, without necessarily having in-depth expertise in each component:
• LLM, agents, MCP, RAG, prompting, code generation;
• Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• GitLab Duo and GitLab DAP;
• Python and API integration;
• Docker, Kubernetes/OpenShift;
• GitLab CI/CD, Jira, Confluence;
• AWS, GCP, S3NS;
• Security and compliance applied to AI;
• Scrum, Kanban and SAFe;
• DevSecOps and SRE best practices.
Desired Profile: The candidate must have a proven technical foundation in development and DevOps with 5+ years of experience.
Practical experience implementing agents, RAGs, or MCPs, or contributing to AI projects, is a significant advantage.
Certifications are welcome. xuezdbg Expected qualities:
• Ability to take initiative and propose decisions and action plans;
• Ability to anticipate technical impacts or associated risks and to raise alerts;
• Ability to understand business challenges, analyze needs, and be proactive in suggesting uses of AI;
• Knowledge of IT and telecommunications security standards and rules;
• Customer-focused approach, active listening, team spirit, and good communication skills;
• Strong ability to learn, simplify, and share knowledge;
• Versatility, autonomy, organization, interpersonal skills, customer service orientation, adaptability, analytical and synthesis skills;
• Rigor and organization;
• Strong analytical and writing skills, including the ability to explain complex topics clearly to non-technical audiences;
• Curiosity, openness, and a collaborative mindset.
Application: CV + cover letter + copies of diplomas to be sent to
Êtes-vous le/la candidat(e) idéal(e) pour cette opportunité ? Assurez-vous de lire la description complète ci-dessous.
The team explores, prototypes, and tools AI applications with a dual objective:
• To leverage AI for the continuous integration pipeline and tooling, primarily GitLab;
• To broadly familiarize the team with these technologies.
The ideal candidate is technically skilled but also capable of understanding business challenges and communicating effectively with non-technical stakeholders.
MISSIONS
• Creation of spikes and POCs around agentic AI: LLM, agents, RAGs, MCPs, prompting, code generation;
• Integration of AI into the CI/CD pipeline and DevSecOps tooling: GitLab, GitLab Duo and DAP in particular, MCPs on the pipeline tools ;
• Design of AI enablers and tools reusable by the train teams;
• Implementation and evaluation of the group's AI building blocks: Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• Design of AI agents and assistants applied to development and DevOps;
• Implementation of RAGs and use of knowledge bases;
• Technological monitoring and evaluation of AI solutions relevant to the train;
• Consideration of security and compliance issues in the use of AI – DevSecOps;
• Development of necessary components: scripts, integrations, APIs;
• Acculturation and dissemination within the train network: training, demonstrations, workshops;
• Writing and popularizing associated documentation in Confluence, for technical and non-technical audiences;
• Supporting train teams in adopting AI usage;
• Contributing to knowledge sharing and collective skills development.
Essential Technical Skills – Mandatory Requirements
• Mastery of agentic AI concepts: LLM, agents, MCP, RAG, prompting;
• Ability to design and integrate AI solutions: agents, RAG, model API calls;
• Strong fundamentals in AI-assisted development and code generation;
• Understanding of the link between AI, CI/CD, and DevSecOps tools, particularly GitLab;
• Ability to understand business challenges and communicate them clearly to non-technical audiences;
• Proficiency in REST APIs and AI service integration;
• Knowledge of the group's AI offerings: Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• Skills in evaluating AI solutions: relevance, robustness, and performance measurement;
• Knowledge of AI assistants for development: GitLab Duo, GitLab DAP;
• Awareness of security and compliance issues related to AI – DevSecOps.
Other key technical
skills:
• Development, particularly Python, and scripting;
• General IT technical knowledge: APIs, architecture, with an operational perspective;
• Knowledge of AWS and GCP clouds;
• Understanding of containerization and execution environments: Docker, Kubernetes/OpenShift;
• Knowledge of Confluence and Jira;
• Experience with agile methodologies (Scrum, SAFe) and teamwork;
• Proficiency in Microsoft Office Suite, Outlook, and Teams;
• Ability to explain complex concepts clearly and facilitate workshops;
• Understanding of how a DevSecOps platform works.
Technological Environment: A good understanding of the following ecosystem is expected, without necessarily having in-depth expertise in each component:
• LLM, agents, MCP, RAG, prompting, code generation;
• Google Gemini, Vertex AI, Antigravity, Anthropic, Mistral;
• GitLab Duo and GitLab DAP;
• Python and API integration;
• Docker, Kubernetes/OpenShift;
• GitLab CI/CD, Jira, Confluence;
• AWS, GCP, S3NS;
• Security and compliance applied to AI;
• Scrum, Kanban and SAFe;
• DevSecOps and SRE best practices.
Desired Profile: The candidate must have a proven technical foundation in development and DevOps with 5+ years of experience.
Practical experience implementing agents, RAGs, or MCPs, or contributing to AI projects, is a significant advantage.
Certifications are welcome. xuezdbg Expected qualities:
• Ability to take initiative and propose decisions and action plans;
• Ability to anticipate technical impacts or associated risks and to raise alerts;
• Ability to understand business challenges, analyze needs, and be proactive in suggesting uses of AI;
• Knowledge of IT and telecommunications security standards and rules;
• Customer-focused approach, active listening, team spirit, and good communication skills;
• Strong ability to learn, simplify, and share knowledge;
• Versatility, autonomy, organization, interpersonal skills, customer service orientation, adaptability, analytical and synthesis skills;
• Rigor and organization;
• Strong analytical and writing skills, including the ability to explain complex topics clearly to non-technical audiences;
• Curiosity, openness, and a collaborative mindset.
Application: CV + cover letter + copies of diplomas to be sent to