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Location
In office (Doha)
Seniority
Architect
Overview
Company
Impact
Profile match
Malomatia is a Qatar-born technology services and digital transformation provider founded to support the nation's public and private sectors. The company specializes in delivering integrated IT solutions, including cybersecurity, cloud services, data and AI, enterprise application modernization, and large-scale contact center operations. By partnering with government agencies, healthcare institutions, and major enterprises, it plays a key role in driving technology-led innovation and economic diversification.

To define technical approach to AI agents, orchestration frameworks, and responsible AI practices while working closely with engineering teams, product managers, and business stakeholders to bring cutting-edge AI capabilities to production.

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
  • 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
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