GenAI Solution Architect

Job Summary:

We value every individual's role in shaping our future. We're looking for candidates who excel in their roles and embody our core behaviors of Trusted Leadership and Distinctive Outcomes. Trusted Leadership focuses on building trust, delivering sustained results, and showing courage and honesty. Distinctive Outcomes emphasize excellence, collaboration, and inclusiveness. We seek self-aware, collaborative individuals committed to continuous learning and delivering quality and integrity.

We are seeking a GenAI Senior Solution Architect to lead the design, development, and deployment of Generative AI-powered applications. This role will focus on architecting scalable AI solutions for cloud-based and hybrid environments, defining AI adoption strategies and best practices, and collaborating with cross-functional teams to drive AI-driven digital transformation. You will play a pivotal role in integrating cutting-edge AI models into enterprise and government systems, ensuring seamless integration into enterprise systems.

This role requires expertise in AI architecture, model hosting, MLOps, and full-stack AI application development, with a focus on security, scalability, and performance.

Roles and Responsibilities:

• Architect and implement Generative AI (GenAI) applications cross functionally and across industries such as government, banking, real estate, and telecommunications.
• Define AI adoption strategies and design scalable AI architectures for both cloud-based and hybrid environments.
• Develop AI-driven automation solutions leveraging CoPilot Studio, Power Automate, and other orchestration tools.
• Build and optimize GenAI frameworks using Retrieval-Augmented Generation (RAG), prompt engineering, and LLM integration.
• Deploy offline and cloud-based LLMs using Nvidia Triton, HuggingFace TGI, vLLM, LiteLLM, and other inference layers.
• Lead full-stack AI application development, ensuring high availability, scalability, and security.
• Collaborate with stakeholders to translate business requirements into AI-enabled solutions.
• Implement MLOps best practices, ensuring efficient model training, deployment, and monitoring.
• Manage CI/CD pipelines, containerization (Docker), and DevOps for AI applications.
• Ensure compliance with AI governance, privacy, and security standards in AI Implementations.
• Provide mentorship and technical leadership to AI engineering teams.

Required Skills:

• AI expertise: Building RAG models, OpenAI agents, Prompt Engineering, Copilot Studio, Python FastAPI Apps, LangChain, CrewAI
• Proven track record of deploying AI solutions at an enterprise level.
• Ability to build applications and expertise in different technology stacks.
• Expertise in Python, FastAPI, Langchain, Langfuse, LlamaIndex.
• Strong experience with AI model hosting, fine-tuning, and API integration.
• Hands-on experience with Cloud Platforms (Azure, AWS, GCP) for AI/ML workloads.
• Proficiency in MLOps, AI Infrastructure Engineering, and Data Engineering.
• Experience in containerization, CI/CD pipelines, and DevOps practices.
• Deep knowledge in LLM architecture, RAG, and inference optimization.
• Knowledge of data privacy, security and ethical AI governance frameworks.
• Understanding of AI governance frameworks and best practices for ethical AI.
• Experience with full-stack development for AI applications if preferable.
• Strong problem-solving skills and ability to work in a fast-paced environment.
• Experience working with government entities and large enterprises is a plus.

Required Language Skills:

• Fluent English
• Arabic proficiency is a plus