Systems Engineering Specialist – DevOps Engineer, AI & Pipeline Automation

AT&T

. Design, build, and maintain Azure DevOps CI/CD pipelines for 5G NF application deployment from lab environments through production .

Posted 10/22/2026full-timeBangalore • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining Azure DevOps CI/CD pipelines, with a strong focus on automation, containerization, and integration of AI-assisted tools for operational efficiency. Proficient in scripting, infrastructure as code, and implementing secure DevOps practices to enhance deployment processes.

Highest-signal resume keywords

Azure DevOps Pipeline DevelopmentScripting in Bash, Python, PowerShellKubernetes Deployment and ManagementAI-Assisted Automation and AnalysisInfrastructure as Code with Ansible

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Linux ExpertiseYAML Template DevelopmentAzure CLI ProficiencyJSON UtilizationBicep and ARM Template CreationKubernetes TroubleshootingAzure Resource ManagementDevOps AutomationRoot-Cause AnalysisSelf-Healing Pipeline Logic

Soft Skills

Collaborative ApproachTechnical CommunicationStakeholder EngagementProblem-SolvingTraining and Mentoring

Tools & Technologies

Azure DevOpsKubernetesAzure OpenAIAnsibleHelm ChartsAzure Key VaultHashiCorp Enterprise VaultMCP ServersAzure Container RegistryAzure Operator Service Manager

Industry Keywords

CI/CD Pipelines5G NF ApplicationsDevOps AutomationAI-Assisted ToolsOperational Telemetry

Tech Stack

Tools & technologies

AnsibleAzureKubernetesLinuxPythonVault

About the role

Key responsibilities & impact

Design, build, and maintain Azure DevOps CI/CD pipelines for 5G NF application deployment from lab environments through production
Develop AI-assisted pipeline automation using LLMs to analyze build failures, deployment issues, pipeline health, and operational telemetry
Build and maintain MCP servers and AI-callable tool integrations for Azure, Azure DevOps, Kubernetes, repositories, and deployments
Create self-healing pipeline workflows with approved remediation, diagnostics, confidence levels, and escalation paths
Partner with client project teams to understand delivery requirements and implement enterprise DevOps automation
Develop reusable YAML templates, pipeline components, scripts, and automation libraries
Integrate pipelines with source control, artifact repositories, approvals, environment gates, testing, security checks, and release governance
Support Kubernetes deployments by troubleshooting failures, configuration issues, container readiness, service health, and environment-specific behavior
Implement CI/CD observability through metrics, logs, dashboards, alerts, failure analysis, and improvement feedback loops
Apply secure DevOps practices for secrets, access control, policies, code review, vulnerability checks, and audit-ready releases
Create AI-assisted root-cause analysis tools and knowledge workflows
Lead technical discussions, working sessions, demos, and hands-on training
Document architecture, operating procedures, automation patterns, troubleshooting guides, and standards
Evaluate emerging DevOps, GenAI, LLM, and MCP capabilities and recommend enhancements

Requirements

What you’ll need

Expert-level Linux experience
Strong scripting skills in Bash, Python, and/or PowerShell
Experience automating manual processes using scripting languages and Infrastructure as Code, such as Ansible
Hands-on experience containerizing, deploying, debugging, and maintaining applications
Expert ability to build Azure DevOps Pipelines from the ground up using YAML
Proficiency with az CLI commands within Azure DevOps Pipelines
Deep understanding of Azure DevOps Repos, including branching, tagging, and environment management strategies
Working knowledge of Azure DevOps Agents
Strong use of JSON and YAML across scripts, Ansible playbooks, and pipelines
Experience with Azure Container Registry, Azure Resource Manager, Endpoints, and Service Principals
Ability to build Azure resources using Bicep and ARM Templates with parameterization
Familiarity with Azure Key Vault and HashiCorp Enterprise Vault for secrets management
Experience with Azure Operator Service Manager
Hands-on experience deploying, managing, and debugging Kubernetes workloads, preferably AKS
Proficiency with kubectl
Ability to diagnose CrashLoopBackOff, image pull errors, resource quota issues, and failed health probes
Experience integrating Kubernetes deployment steps into Azure DevOps Pipelines
Familiarity with Helm charts
Understanding of Kubernetes RBAC and service accounts
Hands-on experience integrating Azure OpenAI or equivalent LLM APIs into automation workflows
Ability to design prompts for pipeline analysis, failure summarization, and root-cause diagnosis
Familiarity with tool/function calling and Retrieval-Augmented Generation
Experience designing and building custom MCP servers
Ability to leverage Azure DevOps REST APIs for pipeline health metrics, flaky tests, and failure patterns
Experience building AI-assisted root-cause analysis workflows against pipeline logs
Capability to design self-healing pipeline logic
Ability to articulate complex technical concepts to stakeholders through presentations and discussions
Collaborative approach across platform, security, and application engineering teams
Bachelor’s degree in Computer Science, Electronics and Communication, Engineering, Information Technology, or a related technical discipline (preferred qualification)
Daily collaboration with U.S. stakeholders, including overlapping work hours
40 weekly hours

Benefits

Comp & perks

Equal employment opportunity and reasonable accommodations for qualified individuals with disabilities
Fair chance hiring practices; background checks initiated only after an offer is made