Sr Ai/MLOps Engineer

Team: AI / Data / EngineeringLocation: Hybrid (Cairo, Egypt)Role Purpose:We are building secure, reliable, and scalable AI-powered solutions for banking. As an MLOps Engineer, you will help productionise machine learning and Generative AI workloads by building reproducible pipelines, robust deployment patterns, and strong observability across AWS.This role is ideal for an engineer who understands fundamentals, critically evaluates new technologies, and enjoys working at the intersection of ML, cloud infrastructure, and Fintech. You will be part of the data team who are responsible for building and deploying the data infrastructure and AI/ML services for the bank.What You’ll DOBuild, improve, and operate ML/GenAI pipelines in production across AWS environments.Own ML/AI services using AWS-native components such as Lambda, S3, SQS, EventBridge,CloudWatch, SageMaker, Fargate, or Bedrock, depending on use case.Design and maintain CI/CD workflows for model and pipeline validation, testing, deployment, and rollbackManage Infrastructure as Code using Terraform to provision and maintain cloud resources consistently across environments.Improve platform reliability through structured logging, tracing, retry handling, and incidentready runbooksSupport governance requirements including security, privacy, auditability, and operationa documentation.Contribute to reusable MLOps standards, tooling, and templates that improve delivery speed and consistency across AI use cases.What We’re Looking ForRequired Experience: 5+ years of experience in MLOps, platform engineering, DevOps, backend engineering, ordata engineering with hands-on responsibility for production systems.A mindset that critically evaluates ideas, aiming for simplicity and reliability, keepingcost,performance and security in mind.Practical experience with AWS and cloud-based deployment of data or ML workloads and event driven architectures.Hands-on experience with modern deployment practices for distributed or serverless systems.Experience with Python for automation, testing, pipeline development, and production support.Experience with Terraform or another Infrastructure as Code tool.Good understanding of monitoring and observability.Clear communication skills and a collaborative approach to working across teams.Preferred / Nice to Have:Understanding of secure engineering practices for PII-sensitive systems.Experience with AWS Bedrock, SageMaker, Textract, or similar managed AI/ML services.Exposure to Generative AI use cases, including prompt-based systems or retrieval-aug Mente generation RAG).Experience working in financial services or another regulated environment.How You’ll WorkAutomation first you look for repeatable, reliable ways to reduce manual work.Reliability focused you build with testing, observability, and safe releases in mind.Security aware you understand the importance of privacy, access control, and auditability in fintech.Collaborative you work well with data scientists, engineers, and platform teams to move from prototype to production. Ownership minded you take responsibility for the quality and operability of the systems you build.What Success Looks Like:ML and AI services are deployed reliably and consistently across environments.Pipelines are well tested, observable, and easy to support.Production issues are easier to detect, diagnose, and recover from.Teams can move faster through reusable tooling, better deployment standards, and clearer operational practices.AI solutions meet the security, compliance, and resilience standards expected ina banking environment.