Data Analytics - Sr. Software Engineer with AI background - Cairo Infomineo

About this role:

We are seeking an experienced and technically strong individual to join us as a Senior AI Software Engineer. In this role, you will take ownership of the design, development, and deployment of AI-powered web applications that serve our internal teams and global clients. You will lead technical initiatives, define architectural standards, and mentor junior engineers, while working across the full stack from application code to AI integration and cloud infrastructure.

Key Responsibilities:

Application Development:

• Architect and lead the development of scalable, production-grade web applications, primarily using Python (FastAPI) for the backend and React, Next.js, or Vue for the frontend, while remaining adaptable to other technologies based on project scope and requirements.
• Define and enforce coding standards, design patterns, and architectural best practices across the engineering team to ensure maintainability and scalability.
• Lead code reviews, provide technical feedback to junior engineers, and actively contribute to building a high-quality engineering culture.
• Collaborate with stakeholders and product teams to translate business requirements into robust technical solutions, owning features end-to-end.

AI & LLM Integration:

• Design and implement complex AI-powered features by integrating LLM APIs and services using frameworks such as LangChain or equivalent, with a focus on reliability and performance in production.
• Own the architecture of Retrieval-Augmented Generation (RAG) pipelines, including document processing, vectorization, semantic search, and query optimization for large-scale enterprise use cases.
• Design, implement, and maintain Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and data sources, enabling context-aware and extensible AI solutions.
• Design and maintain robust REST API integrations with third-party AI services and enterprise SaaS platforms, ensuring data integrity and performance at scale.
• Implement LLM observability and monitoring strategies to ensure transparency, reliability, and continuous improvement of AI features in production environments.

Deployment & DevOps:

• Lead the containerization and cloud deployment of applications, preferably on Google Cloud Platform (GCP) using GKE and Artifact Registry, while remaining open to other cloud environments based on project requirements.
• Design and maintain CI/CD pipelines using GitHub Actions or equivalent tools, applying GitOps principles and automated deployment workflows to ensure reliable and repeatable releases.
• Own the reliability and performance of production environments, proactively identifying bottlenecks and driving resolution of infrastructure and application issues.

Qualifications:

• 4 to 6 years of experience in software engineering and AI development, with a proven track record of delivering production-grade web applications and AI-powered systems.
• Strong proficiency in Python and a backend framework (preferably FastAPI), with solid experience in a modern frontend framework such as React, Next.js, or Vue.
• Deep understanding of LLMs, RAG architectures, and production-grade AI service integration (e.g., OpenAI, Gemini, LangChain or equivalent), including observability and performance monitoring.
• Proven experience designing and implementing Model Context Protocol (MCP) integrations to connect AI models with external tools, APIs, and enterprise data sources.
• Hands-on experience with Docker and cloud deployment on at least one major cloud platform (AWS, Azure, GCP, or equivalent), with familiarity with container orchestration and artifact management services.
• Proven experience designing and maintaining CI/CD pipelines using GitHub Actions or similar tools, with strong command of GitOps workflows and branching strategies.
• Demonstrated ability to lead technical initiatives, mentor junior engineers, and collaborate effectively with product teams and non-technical stakeholders.
• Experience integrating AI outputs into analytical workflows, dashboards, or data pipelines in a client delivery context.
• Bachelor s or Master s degree in Computer Science, Software Engineering, or a related field.

Preferred Skills:

• Experience with agentic AI frameworks such as LangGraph or similar orchestration tools for building multi-step AI workflows.
• Knowledge of advanced prompt engineering, vector database management, and embedding model optimization for production environments.
• Experience with Infrastructure as Code (IaC) tools such as Terraform or Pulumi.
• Relevant certifications such as Google Cloud Professional Developer or similar cloud and AI credentials.

What we offer:

• A competitive compensation and benefits package.
• The opportunity to lead AI and technology initiatives with real global impact.
• A dynamic and supportive work environment that values leadership, innovation, and your contributions.
• Continuous learning and professional development opportunities to propel your career forward in AI and software engineering.