15 days ago
Cairo, EgyptSenior
Responsibilities
- Design and develop agentic AI applications, LLM-driven workflows, and single-agent and multi-agent solutions.
- Implement orchestration, reasoning, planning, memory, tool usage, RAG, embeddings, vector search, and knowledge-base integrations.
- Develop Python backend components and APIs integrating agents with databases, enterprise applications, external services, and business systems.
- Implement security controls, guardrails, evaluation, monitoring, observability, and Responsible AI practices.
- Design evaluations for agent quality, accuracy, reliability, performance, and cost.
- Deploy and operate AI solutions in cloud and containerized environments.
- Collaborate with AI and Data Architects, Data Engineers, Product Owners, and business stakeholders to translate use cases into scalable solutions.
- Own significant technical components, contribute to engineering decisions and standards, create reusable assets, and mentor junior engineers.
Requirements
- At least 5 years of professional experience in software engineering, AI engineering, data engineering, or related technical roles.
- Strong hands-on Python development skills and software engineering fundamentals, including API development, Git, testing, CI/CD, and production-quality coding.
- Practical experience building Generative AI/LLM applications and agentic AI solutions, intelligent workflows, or advanced LLM-based applications.
- Strong understanding of LLMs, prompt engineering, agent orchestration, tool/function calling, RAG architectures, embeddings, vector search, context and memory management, and enterprise integration.
- Experience with at least one agentic AI or Generative AI framework such as LangGraph, LangChain, Microsoft Semantic Kernel, or AutoGen.
- Experience with Docker and/or Kubernetes and at least one major cloud platform: Azure, AWS, or GCP.
- Strong analytical, troubleshooting, problem-solving, independent ownership, and collaboration skills.
- Data engineering experience with data pipelines, ETL/ELT, data integration, SQL, databases, data lakes, lakehouses, warehouses, data quality, metadata, governance, lineage, or security is a significant advantage.
- Preferred qualifications include experience with Azure AI Foundry, Azure OpenAI, AWS Bedrock, vector search or vector databases, MLOps/LLMOps, LLM evaluation and tracing, cloud-native architectures, microservices, Responsible AI, content safety, AI governance, and enterprise AI delivery.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.