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Senior AI Engineer Role Overview We are looking for a Senior AI Engineer who can design, build, and deploy production-ready AI solutions using modern Large Language Models (LLMs), AI agents, and cloud-native architectures. The ideal candidate combines strong software engineering fundamentals with hands-on experience building scalable AI applications, integrating foundation models, and delivering business value through Generative AI. Key Responsibilities • Design, develop, and maintain AI-powered applications using Large Language Models (LLMs) and Generative AI technologies. • Build AI agents and Retrieval-Augmented Generation (RAG) solutions to enable intelligent workflows and knowledge-based applications. • Integrate leading AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or similar services. • Develop scalable backend services and APIs using Python and modern frameworks such as FastAPI. • Collaborate with frontend engineers to deliver end-to-end AI applications using technologies such as React. • Design prompt engineering strategies to improve model accuracy, reliability, and user experience. • Implement intelligent routing, semantic search, vector databases, and knowledge retrieval solutions. • Deploy and manage cloud-native AI applications using AWS and Infrastructure as Code tools such as Terraform. • Build and maintain CI/CD pipelines, containerized applications, and cloud infrastructure using Docker and DevOps best practices. • Evaluate emerging AI frameworks, tools, and models to continuously improve platform capabilities. • Collaborate with Product Managers, Architects, and Engineering teams to translate business requirements into scalable AI solutions. • Mentor engineers and contribute to technical leadership, architecture discussions, and engineering best practices. Required Qualifications • 10+ years of experience in Software Engineering with recent hands-on experience building Generative AI solutions. • Strong experience with Python and REST API development. • Experience developing production AI applications using Large Language Models (LLMs). • Hands-on experience with AI agent frameworks such as LangChain, CrewAI, or similar technologies. • Experience implementing Retrieval-Augmented Generation (RAG) architectures. • Experience integrating AI platforms such as Azure OpenAI, Amazon Bedrock, Google Vertex AI, or equivalent services. • Strong understanding of prompt engineering techniques and AI application design patterns. xebia.com • Experience developing scalable cloud applications on AWS. • Experience with Docker, Terraform, CI/CD pipelines, and Infrastructure as Code. • Experience with SQL and NoSQL databases. • Familiarity with React or modern frontend technologies. • Experience working within Agile software development environments. • Strong understanding of software architecture, API design, and distributed systems. • Experience working in cross-functional and multicultural teams. Working Style • Strong communication skills: able to clearly explain complex AI concepts to both technical and non-technical audiences. • Proactive mindset: identifies opportunities for innovation and continuously explores new AI technologies. • Ownership and accountability: takes responsibility for delivering reliable, scalable, and maintainable AI solutions. • Collaborative attitude: works effectively across product, engineering, architecture, and business teams. • Adaptability: thrives in a rapidly evolving AI landscape and embraces continuous learning. • Attention to detail: prioritizes quality, security, observability, and responsible AI practices. • Customer-oriented thinking: focuses on solving real business problems through practical AI solu