Manager - AI Engineering
At a glance
Manager-level AI Engineering role at Fa Ewjt Saasfaprod1. Bengaluru · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and tune CI/CD workflows in Azure DevOps and GitHub Actions for AI, data and application workloads
- Run AI and data platforms on Azure Kubernetes Service, packaging deployments with Docker and Helm
- Set up Azure compute, networking, storage and security, including secrets controls and cloud cost tracking
- Support ETL and model releases with data pipelines, production deployment, monitoring and ML engineer collaboration
- Check platform health and load-test results, then automate releases and improve reliability and performance
What you bring
- You have three to six years in AI platform enablement, DevOps, cloud engineering or a related area
- You have supported production systems on Microsoft Azure
- You bring practical experience with CI/CD automation, container platforms and cloud-native architectures
- A bachelor's degree is required, preferably in engineering, computer science or a related discipline
Who this fits
This role suits someone who works across cloud operations, data pipelines and machine learning delivery, with an automation and reliability focus. It is based in Bengaluru and follows a hybrid arrangement.
From the employer
A results-driven AI Engineer with strong DevOps 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 DevOps, cloud infrastructure, and machine learning enablement, with a clear focus on automation, reliability, and secure delivery.
Key Responsibilities
- Build, manage, and optimize CI/CD pipelines using Azure DevOps and GitHub 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 / BlazeMeter 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.
- 3 to 6 years of relevant experience in AI platform enablement, DevOps, 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)
- Technical Skills
- Azure DevOps Pipelines and GitHub 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, PowerShell, 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 DevOps, data, and AI engineering domains
-
Continuous improvement and automation-first mindset