Artificial intelligence engineer

Job Summary

We are looking for a results-driven AI Engineer with strong Dev Ops and Cloud Engineering expertise to support the design, deployment, and operation of scalable, production-grade AI and data platforms on Microsoft Azure. The ideal candidate brings hands-on experience working at the intersection of Dev Ops, cloud infrastructure, and machine learning enablement, with a clear focus on automation, reliability, and secure delivery.

This role partners closely with application, data, and machine learning teams to ensure AI solutions are deployed efficiently, monitored effectively, and operated at scale in an Agile environment.

Key Responsibilities

Build, manage, and optimize CI/CD pipelines using Azure Dev Ops and Git Hub Actions for AI, data, and application workloads. Deploy and operate AI-enabled and data platforms on Azure Kubernetes Service (AKS) using Docker and Helm. Provision and manage Azure infrastructure including compute, networking, storage, and security services. Enable MLOps and data pipelines by supporting ETL workflows using Azure Data Factory and Databricks. Implement secure configuration and secrets management using Azure Key Vault. Monitor platform health, performance, and availability using Azure Monitor and Log Analytics. Conduct performance and load testing using JMeter / Blaze Meter and drive optimization actions. Collaborate with ML engineers to support model packaging, versioning, deployment, and monitoring in production. Support Agile delivery through automation, release coordination, and continuous improvement. Track and optimize cloud infrastructure costs across environments.

Required Technical Skills

Azure Dev Ops Pipelines and Git Hub Actions YAML-based CI/CD automation Azure Kubernetes Service (AKS) Docker and Helm Azure App Service, Virtual Machines, VNet Azure Data Lake Storage (ADLS Gen2) Azure SQL Database Azure Container Registry (ACR) Azure Key Vault Azure Data Factory and Databricks Azure Monitor and Log Analytics Bash, Power Shell, Python (basic)

Professional Skills

Strong problem-solving and analytical mindset Excellent collaboration and stakeholder communication skills Experience working in Agile / Scrum teams High ownership, accountability, and execution focus Ability to work across Dev Ops, data, and AI engineering domains Continuous improvement and automation-first mindset

Experience

3 to 6 years of relevant experience in AI platform enablement, Dev Ops, Cloud Engineering, or related roles Proven experience supporting production workloads on Microsoft Azure Hands-on exposure to CI/CD automation, container platforms, and cloud-native architectures

Education

Bachelor's degree required (Engineering, Computer Science, or related discipline preferred)