AI Engineer (Expert) 2073

SUMMARY:
Are you passionate about building intelligent solutions and shaping the future of AI? Join our dynamic global team as an AI Engineer and play a key role in developing cutting-edge AI and MLOps solutions within a modern, fast-paced environment.

POSITION INFO:
Key requirements:
Cloud Infrastructure

• Experience with Infrastructure as Code using Terraform.
• Strong experience with CI/CD and automation
• Containerisation & Orchestration such as Kubernetes, MLflow or Docker
• Strong knowledge of AWS Services such as Stepfunctions, EC2, Lambda etc.

• Strong understanding of Python syntax and principles of clean, reusable code.
• Understanding of Python frameworks and libraries e.g. Pandas and NumPy

• Experience developing, deploying, and managing serverless applications using AWS Lambda
• Proficiency in writing unit and integration tests for AWS Lambda functions to ensure functionality, performance, and reliability.

• Experience with Git repositories and code management (e.g. GitHub)
• Proficiency in using Git for version control and collaboration.

• Experience with testing tools like pytest for creating and maintaining unit tests.
• Ability to implement automated testing pipelines to ensure code reliability.

• API designing principles and best practices.
• Experience in working with RESTful APIs and understanding how to consume and create APIs.
• Familiarity with API management tools, such as Apigee, for efficient and secure API integration.

• Visual studio code
• AI Coding assistants such as Github Copilot and Windsurf.
• Any additional responsibilities assigned in the Agile Working Model (AWM) Charter

• Develop and integrate MLOps pipelines for scalable AI solutions.
• Provide support for low-code/no-code solutions in business walk-in sessions.
• Implement processes for continuous training and inference improvements.
• Write production-level Python code with clean, reusable principles.
• Leverage cloud technologies (AWS, Terraform, Kubernetes, etc.) to build machine learning pipelines.
• Ensure security compliance and implement best practices in AWS.
• Stay ahead with the latest advancements in Machine Learning, MLOps, and Generative AI.
• Manage and enhance monitoring, automation, and alerting tools