AI Engineer

An ideal candidate would also have the following skills:Minimum requirements are strong understanding of cloud architecture (IAM, key vaults etc.) and hands-on experience developing serverless RESTful API's and web frontend using Angular in Azure/AWS in the past 3 years (prefer Azure, consider AWS) that ideally have some experience or interest in learning AI cognitive services. - Example of Serverless RESTful API's for AWS is API Gateway with Azure is Azure Functions. Other serverless functions for AWS are Lambas, and DynamoDB.SQL/NoSQL databases (required)We work in cloud services using serverless functions (required)container environments (preferred) - examples are Kubernetes (K8's) (Azure K8's is AKS, AWS K8's is ECS)service bus/event hub (preferred) -Azure Event Hub manages real time data ingestion from multiple pipelines. Azure Service Bus is used to. decouple applications and services from eachother for load balancing, safe routing and transferring data/control across services and application boundries, transactional work that requires high reliability.AWS services like service bus are called EventBridge, event hub for AWS is called Amazon Kinesis.OCR/ICR (willing to learn) - optical character recognition / intelligent character recognitioncognitive search (willing to learn)computer vision (willing to learn)speech to text transcription (willing to learn)OpenAI (willing to learn) Minimum requirements are strong understanding of cloud architecture (IAM, key vaults etc.) and hands-on experience developing serverless RESTful API's and web frontend using Angular in Azure/AWS in the past 3 years (ie. full stack). NOT looking for ML Ops candidates or data scientists, but if they have ML experience along with core engineering experience that would be the ideal experience (ie. engineer first + ML). REQUIRED EDUCATION Bachelors degree or equivalent #J-18808-Ljbffr