at Capgemini
ConsultanciesPosted 6 days ago
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**Agentic AI Technical Leader**: Lead enterprise-level GenAI and agent-based solutions, overseeing architecture, delivery, and technical direction. Design agent-based workflows and RAG architectures (Agentic AI, LLM), make architectural decisions for scalability and performance. Stay hands-on with Python, LLMs, and agent frameworks (LangChain, LlamaIndex). Lead and mentor teams, drive responsible AI practices. Partner with platform and MLOps teams, engage clients in technical discussions. Requires 12+ years in AI engineering, proven GenAI/Agentic AI delivery, strong Python skills, and experience with agent frameworks. Fluency in Arabic and English essential.
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Full Job Description
Job Overview
We are seeking a senior Agentic AI Technical Leader to lead the architecture and delivery of enterpriselevel GenAI and agentbased solutions. This role owns Agentic AI design, delivery quality, and technical direction, supported by platform engineers, MLOps teams, and sales.
Key Responsibilities
Agentic AI Architecture & Delivery
- Lead the design and production delivery of Agentic AI and LLMbased systems in enterprise environments.
- Design agentbased workflows and RAG architectures for real business use cases.
- Make architectural decisions to ensure scalability, reliability, security, and performance.
HandsOn Technical Leadership
- Stay handson where it matters: core agent logic, prototypes, code reviews, and critical troubleshooting (Python).
- Guide the selection and use of LLMs (proprietary and opensource) based on usecase needs.
- Apply and extend agent frameworks (e.g., LangChain, LangGraph, LlamaIndex).
Team Leadership
- Lead and mentor AI, ML, and Data Science engineers, setting standards and best practices.
- Drive responsible AI practices and technical excellence across delivery teams.
Platforms & MLOps Collaboration
- Partner with platform and MLOps teams to operationalize solutions on cloud AI platforms (Azure, AWS, or GCP).
- Guide CI/CD, monitoring, evaluation, and production readiness.
Client Engagement
- Act as a technical lead and consultant in selected client discussions and solution shaping.
- Translate AI architectures into business outcomes.
Required Experience & Skills
MustHave
- 12+ years in software/data/AI engineering with a strong recent focus on Generative & Agentic AI.
- Proven experience delivering agentbased or LLMdriven systems in production.
- Strong Python expertise and modern AI engineering practices.
- Handson experience with agent frameworks and RAG.
- Experience leading technical teams and owning architectural decisions.
- Excellent communication and executivelevel articulation.
- Fluent Arabic & English.
Strong Plus
- Multiagent system design.
- Familiarity with Model Context Protocol (MCP) concepts or similar agenttool integration patterns.
- Experience with cloud AI platforms (Azure AI, AWS Bedrock, Vertex AI).
- Consulting or clientfacing delivery experience.
