Senior AI Engineer / Agentic AI Architect

About CodeNinja is a global software and AI infrastructure company delivering full-stack technology solutions across AI, software engineering, data, and digital transformation. With operations across Saudi Arabia and global technology hubs, CodeNinja works with organizations across multiple industries to deliver technology solutions that support business transformation and innovation. Our teams work across areas including AI, software engineering, data and analytics, cloud, enterprise technology, and digital transformation. About the Role In this role, you will deliver production-grade AI applications with a focus on scalability, security, observability, governance, and performance. You will work across Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI. The ideal candidate will have strong software engineering fundamentals and deep expertise in LLMs, RAG, Agentic AI, and modern AI engineering practices. They will have 8 12+ years in software engineering, including 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI. Key Responsibilities Design and develop enterprise-grade AI solutions using modern LLMs and Agentic AI frameworks. Architect multi-agent systems capable of planning, reasoning, tool usage, and workflow orchestration. Build production-ready RAG platforms integrating structured and unstructured enterprise data. Design scalable APIs and AI services using Python and modern backend frameworks. Implement robust evaluation frameworks for LLM quality, safety, and performance. Optimize AI applications for latency, throughput, and infrastructure cost. Deploy and manage open-source LLMs in production environments. Collaborate with architects, product owners, business analysts, and DevOps teams to deliver enterprise AI platforms. Ensure compliance with enterprise security, governance, and responsible AI practices. Mentor engineering teams and contribute to AI best practices and reusable frameworks. Expected Deliverables The selected candidate should be capable of independently designing and delivering: Enterprise AI platforms Multi-agent AI systems RAG-based knowledge assistants AI copilots LLM evaluation frameworks Production-ready AI APIs AI observability and monitoring solutions Secure, scalable, and cost-optimized AI deployments suitable for enterprise production environments. Requirements Required Qualifications & Skills Experience 8 12+ years of experience in Software Engineering. 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI. AI / Machine Learning Strong understanding of: Machine Learning Deep Learning NLP Transformer architectures Large Language Models (LLMs) Embedding models Software Engineering Expert-level Python programming. Strong software engineering fundamentals. Experience building production-grade backend systems. RESTful API and microservices development. Oracle MongoDB Redis Elasticsearch / OpenSearch Soft Skills Strong analytical and problem-solving skills. Excellent communication and stakeholder management. Ability to lead technical discussions and architecture reviews. Experience mentoring engineering teams. Ability to work in Agile delivery environments. Banking & Industry Experience (Nice to Have) Banking or Financial Services domain experience. Experience with enterprise AI governance and Responsible AI frameworks. Knowledge of SAMA, NCA, or other financial regulatory environments. Experience building AI copilots and enterprise AI assistants. Knowledge of OCR, document intelligence, and intelligent automation. Experience integrating AI solutions with BPM/workflow platforms such as Appian, Camunda, or Pega. Education & Certifications Bachelor's degree in Computer Science, Artificial Intelligence, Information Technology, Engineering, or a related field. The following professional certifications are an advantage: Google Professional Machine Learning Engineer Microsoft Azure AI Engineer Associate AWS Certified Machine Learning Specialty Databricks Machine Learning Professional NVIDIA AI Certifications OpenAI or Anthropic ecosystem certifications (where applicable) Key Competencies Agentic AI | Multi-Agent Systems | Large Language Models (LLMs) | RAG | Vector & Graph Databases | LLM Evaluation | Guardrails & Observability | Prompt Engineering | LLM Deployment & Inference | MLOps | Python | APIs & Microservices | Cloud AI Platforms | Responsible AI Benefits What We Offer Competitive compensation based on experience and qualifications. Opportunity to work on enterprise-scale technology and digital transformation projects. Exposure to banking, financial services, AI, data, and emerging technology environments. Professional growth and learning opportunities. Collaborative and technically driven work environment. Opportunity to work with experienced technology and consulting professionals. Disclaimer This job description is intended to convey information essential to understanding the scope of the role and is not exhaustive of all responsibilities, skills, or qualifications required. CodeNinja reserves the right to modify duties and responsibilities at any time.

Desired Candidate Profile

Bachelor's degree in Computer Science, Artificial Intelligence, Information Technology, Engineering, or a related field. 8 12+ years of experience in Software Engineering. 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI. Expert-level Python programming. Strong software engineering fundamentals. Experience building production-grade backend systems. RESTful API and microservices development. Async programming and scalable architectures. Experience with FastAPI, Flask, or similar frameworks.