ML Ops/Cloud Engineer

You will be joining a team at EG dedicated to developing and maintaining an AI assistance solution for service and support. As an ML Ops / Cloud Engineer with 5 years of experience, your responsibilities will include designing, implementing, and managing the cloud infrastructure on AWS, deploying AI models at scale, and ensuring the operational excellence of our AI products based on AWS Large Language Models (LLMs). **Role Overview:** You will be a part of a newly set up team within the EG IT department, focused on supporting clients and employees with their daily activities. This team will closely cooperate with the ServiceNow team as the AI-based product will be integrated with ServiceNow tool. **Key Responsibilities:** - Design, implement, and manage scalable, secure, and reliable cloud infrastructure on AWS for AI model deployment, monitoring, and maintenance. - Automate deployment pipelines, CI/CD workflows, and model updates for continuous delivery and integration. - Optimize resource utilization on AWS for balancing performance and cost-efficiency. - Monitor, troubleshoot, and resolve operational issues related to AI models, data pipelines, and infrastructure. - Implement logging, alerting, and performance tracking for high availability and reliability of AI services. - Collaborate with Data Scientists and Software Engineers to translate ML models into production-ready solutions. - Ensure compliance with security policies and data governance standards within AWS infrastructure. - Stay updated on advancements in ML Ops, cloud engineering, and AI deployment best practices. **Qualifications Required:** - Proven experience in ML Ops, cloud engineering, or DevOps roles, preferably with AWS cloud services. - Strong expertise with AWS infrastructure services like SageMaker, Bedrock, Lambda, EC2, S3, CloudFormation, and related tools. - Experience with containerization technologies (Docker, Kubernetes) and orchestration. - Hands-on skills in scripting (Python, Bash) and automation frameworks. - Knowledge of CI/CD pipelines, monitoring tools, and infrastructure-as-code practices. - Understanding of ML lifecycle management, model deployment, and optimization. - Good problem-solving skills with a focus on operational stability and scalability. **Preferred Qualifications:** - Experience working with AI/ML models, especially LLMs, in cloud environments. - Background in support or chatbot deployment scenarios. - Familiarity with security and compliance standards in cloud environments. - Demonstrated leadership in managing cross-cultural, international teams within agile environments. - Familiarity with cloud security standards and data governance. **Additional Details:** You can expect to work in a professional and business-driven environment with exciting projects, alongside talented and committed colleagues who value collaboration and active knowledge sharing. The role also offers opportunities for personal and professional development, including targeted training courses in the EG Academy, and best-in-industry employee benefits.,