Senior Consultant - AI Solution Architect

Responsibilities

• Lead AI solutions design and implementation • Serve as the primary technical advisor on generative AI initiatives • Lead 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 and architect AI agent systems and multi-agent workflows for enterprise use cases • Evaluate and implement agent frameworks including LangGraph, Microsoft Agent Framework, OpenAI Agents SDK, Google Agent-to-Agent (A2A), and emerging standard • Architect tool-use patterns, function calling, MCP, and agent-to-agent communication protocols • Design for agent observability, debugging, and human-in-the-loop workflows • Design retrieval-augmented generation architectures and architect vector database solutions, embedding strategies, implement chunking strategies, hybrid search, and re- ranking approaches for optimal retrieval performance • Design knowledge graphs and structured data integration with generative AI systems • Lead architecture decisions across cloud AI platforms including Azure AI Foundry, Google Vertex AI, OpenAI APIs, and open-source Gen AI models • Design prompt management, versioning, and optimization pipelines • Architect for multi-model strategies, model routing, and fallback patterns • Establish patterns for cost optimization, latency management, and scaling LLM workloads • Define comprehensive evaluation frameworks for LLM applications and agent systems • Implement automated evaluation pipelines using frameworks such as RAGAS, DeepEval, and custom evaluation harnesses • Establish benchmarks for response quality, factual accuracy, task completion, and user satisfaction • Champion responsible AI practices including safety, fairness, transparency, and privacy • Implement guardrails, content filtering, and output validation systems • Design for prompt injection prevention, data leakage protection, and secure agent execution • Ensure compliance with emerging AI regulations and industry standards

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred. Arabic Speaker. • 8+ years of experience in software engineering or architecture roles • 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 of the following: LangChain/LangGraph, Microsoft Semantic Kernel/Agent Framework, OpenAI Agents SDK, Google Vertex AI Agent Builder • Proven experience designing and implementing Advanced RAG Systems and Agentic AI • Proficiency in Python and experience with async programming patterns • Hands-on experience with cloud AI platforms (Azure AI Foundry or Google Vertex AI) • Strong understanding of Gen AI models’ fundamentals including prompting, fine-tuning, context windows, and token economics Preferred Qualifications • Experience implementing Model Context Protocol (MCP), Google Agent-to-Agent (A2A) protocol, and multi-agent communication patterns • Experience building AI Evals pipelines and AI quality assurance systems • Knowledge of advanced RAG techniques: query decomposition, multi-hop reasoning, GraphRAG • Experience with AI observability tools • Background in AI safety, red-teaming, or responsible AI implementation.
• Skills & Competencies • Systems thinking with ability to design for complexity and emergence in agentic systems • Strong communication skills to convey AI concepts to diverse audiences • Pragmatic approach balancing innovation with production readiness • Ability to rapidly learn evolving AI technologies • Commitment to ethical AI development and user safety • Collaborative mindset with ability to influence across organizational boundaries

About Company

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