Senior Consultant - AI Solution Architect

Job Description

Architecture and Delivery

• Lead AI solution design, implementation, proof-of-concept development, and architectural decision records.
• Mentor engineering teams on agentic AI patterns and best practices.
• Evaluate emerging technologies and maintain technical roadmaps.
• Design AI agent systems and multi-agent workflows for enterprise use cases.
• Evaluate and implement agent frameworks, tool-use patterns, function calling, MCP, and agent-to-agent protocols.
• Design observability, debugging, and human-in-the-loop workflows for agents.

RAG and Knowledge Systems

• Design retrieval-augmented generation architectures and vector database solutions.
• Define embedding, chunking, hybrid search, and reranking strategies for retrieval performance.
• Design knowledge graphs and structured-data integration with generative AI systems.

Cloud and Model Architecture

• Lead architecture decisions across Azure AI Foundry, Google Vertex AI, OpenAI APIs, and open-source generative AI models.
• Design prompt management, versioning, and optimization pipelines.
• Architect multi-model strategies, model routing, fallback patterns, and scalable LLM workloads.

Evaluation and Responsible AI

• Define evaluation frameworks and automated pipelines for LLM applications and agent systems.
• Establish benchmarks for response quality, factual accuracy, task completion, and user satisfaction.
• Implement guardrails, content filtering, output validation, prompt-injection prevention, data-leakage protection, and secure agent execution.
• Ensure compliance with emerging AI regulations and industry standards.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field; a master's degree is preferred.
• Arabic language capability.
• At least 8 years of experience in software engineering or architecture roles.
• At least 3 years of hands-on experience building LLM-powered applications in production.
• Deep expertise in AI agent architectures, orchestration patterns, and workflow design.
• Strong experience with at least two listed agent frameworks.
• Proven experience designing and implementing advanced RAG systems and agentic AI.
• Proficiency in Python and asynchronous programming patterns.
• Hands-on experience with Azure AI Foundry or Google Vertex AI.
• Strong understanding of prompting, fine-tuning, context windows, and token economics.

Preferred Qualifications

• Experience implementing MCP, Google A2A, and multi-agent communication patterns.
• Experience building AI evaluation pipelines and AI quality assurance systems.
• Knowledge of query decomposition, multi-hop reasoning, and GraphRAG.
• Experience with AI observability tools.
• Background in AI safety, red-teaming, or responsible AI implementation.

Skills and Competencies

• Systems thinking for designing complex and emergent agentic systems.
• Strong communication skills for explaining AI concepts to diverse audiences.
• Pragmatic approach that balances innovation with production readiness.
• Ability to rapidly learn evolving AI technologies.
• Commitment to ethical AI development and user safety.
• Collaborative mindset with the ability to influence across organizational boundaries.

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