AI Engineer

What We Need

We are seeking a motivated mid-level AI Engineer to join Oivans AI core team as part of our AI-first transformation initiative, focusing on implementing and deploying production-ready AI systems while championing AI adoption across our organization. You will play a pivotal role in building practical AI solutions using existing large language models (LLMs) and establishing the foundation for Oivan's AI-driven culture.

As an AI Engineer at Oivan, you will work with established AI platforms and LLMs, implement RAG systems for enhanced business intelligence, develop AI agents that solve real organizational challenges, and serve as an AI evangelist who helps teams across departments understand and leverage AI capabilities. Your work will directly contribute to Oivan's strategic goal of becoming the leading AI-first technology partner in the MENA region, with particular focus on government, proptech, telecoms, and enterprise sectors.

What You'll Do

AI System Development

• Implement and deploy RAG systems that connect LLMs with Oivan's internal knowledge bases, documentation, and business data sources
• Build production-ready AI agents using established frameworks like LangChain, LangGraph for specific business use cases
• Develop and maintain AI-powered applications that integrate seamlessly with existing business workflows and systems
• Deploy conversational AI solutions for internal process automation, employee assistance, and knowledge management
  
  

AI Agent Implementation & Integration

• Design and implement AI agents that automate routine business processes, from customer inquiries to internal operations
• Build tool integration capabilities for agents to interact with Oivan's existing software stack, databases, and business applications
• Support Oivans SecOps team to monitor and evaluate systems to ensure AI agents perform reliably in production environments
• Implement feedback loops that continuously improve agent performance based on real-world usage patterns
  
  

Organizational AI Culture Building

• Champion AI adoption across departments by demonstrating practical AI applications that solve real business problems
• Conduct internal workshops and training sessions to help colleagues understand AI capabilities and identify opportunities for AI integration
• Collaborate with cross-functional teams to identify high-impact use cases where AI can streamline operations or enhance decision-making
• Create documentation and best practices that enable other team members to understand and contribute to AI initiatives
  
  

Technical Infrastructure & Deployment

• Support our SecOps with deployments of AI systems and agents in cloud environments using platforms like AWS, Azure, or Google Cloud with focus on reliability and scalability
• Support our SecOps with secure AI practices including data privacy protection, bias monitoring, and system reliability safeguards
• Support our SecOps to establish monitoring systems for production AI performance, usage analytics, and system health tracking
• Optimize AI system performance for cost-effectiveness while maintaining quality and responsiveness
  
  

What You Have

Technical Expertise

• Programming Languages: Proficiency in Python with experience in AI frameworks (TensorFlow, PyTorch, LangChain)
• LLM Integration: Hands-on experience working with existing LLM APIs (OpenAI, Anthropic, Google, etc.), Model Context Protocol and implementing LLM-powered applications
• RAG Systems: Practical experience with retrieval-augmented generation systems and working with vector databases
• Production Deployments: Experience with AI applications in production environments with monitoring and maintenance capabilities
• System Integration: Ability to integrate AI solutions with existing business systems, databases, and workflows
  
  

AI Implementation Experience

• Agent Development: Experience building AI agents that can perform specific business tasks and interact with external tools and systems
• API Development: Proficiency in creating and maintaining APIs that expose AI capabilities to business applications
• Performance Optimization: Understanding of how to optimize AI systems for production use, including cost management and response time optimization
  
  

Organizational & Communication Skills

• Cross-functional Collaboration: Ability to work with non-technical stakeholders to identify AI opportunities and requirements
• Training & Mentoring: Experience or enthusiasm for teaching others about AI concepts and helping teams adopt new technologies
• Documentation: Technical writing skills for creating user guides, best practices, and system documentation
  
  

Education & Experience

• Bachelors degree in Computer Science, Engineering, Data Science, or related field
• 3-5 years of experience in AI/ML engineering, software development, and related technical roles
• Demonstrated experience with production AI system deployment and maintenance
• Proven track record of working with LLMs and building practical AI applications
  
  

Preferred Qualifications

• Experience in organizational change management or technology adoption initiatives
• Experience with MLOps practices and tools for production AI system management
• Understanding of AI ethics, bias detection, and responsible AI practices
• Previous experience in consulting or internal enablement roles
  
  

What We Offer

Oivan company culture is reflective of our core values: Responsibility, Reliability, and Fellowship. The decisions we make today influence our tomorrow. We are sincere in our responsibility towards our employees, customers and the environment. Fellowship unites us as an international community of thinkers and doers. Throughout our hiring process, you will have access to a broad representation of the Oivan team in order to get to know us as we learn about you. Feel free to contact [email protected] for any questions.

Who We Are

At Oivan, we appreciate different lifestyles and cultural backgrounds. We welcome diversity as a strength. We consider all applications equally regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. On our equitable compensation model, we routinely analyse and close out pay disparities when we find them, including an annual compensation review.