Specialist System Engineering - DevOps Engineer — AI & Pipeline Automation

Location: Navigator Bldg:Intl Tech Park, India

**Job Responsibilities**

• Design, build, and maintain Azure DevOps CI/CD pipelines that support 5G NF application deployment from lab environments through production with repeatable, secure, and automated promotion workflows.

• Develop AI-assisted pipeline automation capabilities that use LLMs to analyze build failures, deployment issues, pipeline health, and operational telemetry.

• Build and maintain MCP servers and AI-callable tool integrations that expose Azure, Azure DevOps, Kubernetes, repository, and deployment capabilities through controlled automation interfaces.

• Create self-healing pipeline workflows that can detect common failure patterns, trigger approved remediation steps, and provide clear diagnostics, confidence levels, and escalation paths.

• Partner with client project teams to understand delivery requirements, architect CI/CD solutions, and implement automation patterns aligned with enterprise DevOps standards.

• Develop reusable YAML templates, pipeline components, scripts, and automation libraries that standardize CI/CD delivery across applications, environments, and teams.

• Integrate pipeline workflows with source control, artifact repositories, approvals, environment gates, testing frameworks, security checks, and release governance processes.

• Support Kubernetes-based deployments by troubleshooting deployment failures, configuration issues, container readiness, service health, and environment-specific pipeline behavior.

• Implement observability for CI/CD systems, including pipeline metrics, logs, dashboards, alerts, failure trend analysis, and continuous improvement feedback loops.

• Apply secure DevOps practices for secrets handling, access control, policy enforcement, code review, vulnerability checks, and audit-ready release execution.

• Create AI-assisted root-cause analysis tools and knowledge workflows that help engineering teams quickly identify probable causes and recommended next actions.

• Lead technical discussions, working sessions, demos, and hands-on training to improve DevOps maturity and enable client teams to adopt AI-enabled pipeline automation.

• Document architecture, operating procedures, automation patterns, troubleshooting guides, and standards to ensure consistent adoption and long-term maintainability.

• Continuously evaluate emerging DevOps, GenAI, LLM, and MCP capabilities and recommend practical enhancements that improve delivery speed, quality, reliability, and operational efficiency.

**Job Qualifications / Required Qualifications**

Linux & Scripting Fundamentals

• Expert-level Linux experience with strong scripting skills in Bash, Python, and/or PowerShell

• Proven ability to automate manual processes using scripting languages and Infrastructure as Code (e.g., Ansible)

• Hands-on experience containerizing, deploying, debugging, and maintaining applications

Azure DevOps & Pipeline Engineering

• Expert ability to build ADO Pipelines from the ground up using YAML

• Proficiency with az cli commands within ADO Pipelines to interact with Azure Resources

• Deep understanding of ADO Repos including branching, tagging, and environment management strategies

• Working knowledge of ADO Agents – their purpose, capabilities, and limitations

• Strong use of JSON and YAML as data formats across scripts, Ansible playbooks, and pipelines

Azure Platform & Infrastructure

• Experience with Azure Container Registry (ACR) to import, tag, and extract images and charts within pipelines

• Understanding of Azure Resource Manager, Endpoints, and Service Principals

• Ability to build Azure Resources using Bicep and ARM Templates with emphasis on parameterization

• Familiarity with Azure Key Vault (AKV) and Hashi Corp Enterprise Vault (HCEV) for secrets management

• Experience with Azure Operator Service Manager (AOSM)

Kubernetes & Container Orchestration

• Hands-on experience deploying, managing, and debugging workloads on Kubernetes (AKS preferred)

• Proficiency with kubectl for inspecting pods, logs, events, and resource states during pipeline-triggered deployments

• Ability to diagnose and resolve common deployment failures including CrashLoopBackOff, image pull errors, resource quota issues, and failed health probes

• Experience integrating Kubernetes deployment steps into ADO Pipelines including rollout strategies, namespace management, and environment promotion

• Familiarity with Helm charts for packaging and deploying applications through pipelines

• Understanding of Kubernetes RBAC, service accounts, and their role in secure pipeline-based deployments

AI & LLM Integration

• 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 agent-based AI patterns including tool/function calling and Retrieval-Augmented Generation (RAG)

• Experience designing and building custom MCP servers to expose internal APIs and data as AI-callable tools

Pipeline Intelligence & Analysis

• Ability to leverage ADO REST APIs to surface pipeline health metrics, flaky tests, and failure patterns

• Experience building AI-assisted workflows for root-cause analysis against pipeline logs

• Capability to design self-healing pipeline logic - detect, diagnose, remediate, and re-trigger

Communication & Collaboration

• Demonstrated ability to articulate complex technical concepts, solutions, and standards to stakeholders across varying skill levels - through both presentations and discussions

• Collaborative approach to working across platform, security, and application engineering teams

**Preferred Qualifications**

• Minimum bachelor’s degree in Computer Science, Electronics and Communication, Engineering, Information Technology, or a related technical discipline.

• Demonstrated experience building enterprise-grade Azure DevOps pipeline automation using YAML, reusable templates, environment gates, approvals, and automated release promotion workflows.

• Hands-on experience integrating AI or LLM capabilities into DevOps workflows for build failure analysis, pipeline summarization, root-cause diagnosis, and recommended remediation.

• Experience designing or operating MCP servers, AI-callable tools, function-calling frameworks, or controlled automation interfaces that interact with Azure, ADO, repositories, Kubernetes, or internal APIs.

• Practical experience with self-healing or intelligent automation that detects recurring failure patterns, triggers approved remediation actions, and provides diagnostics with clear escalation paths.

• Strong working knowledge of Kubernetes-based application deployments, Helm charts, container registries, kubectl troubleshooting, rollout strategies, and secure service account/RBAC practices.

• Experience using Azure services such as Azure Container Registry, Azure Key Vault, Service Principals, ARM/Bicep templates, Azure CLI, and Azure Operator Service Manager within automated delivery pipelines.

• Familiarity with observability and pipeline intelligence practices, including pipeline health metrics, log analysis, flaky test detection, dashboards, alerts, and continuous improvement feedback loops.

• Exposure to GenAI patterns such as prompt engineering, Retrieval-Augmented Generation, tool/function calling, agentic workflows, and responsible use of AI guardrails in automation scenarios.

• Ability to lead technical working sessions, document standards and operating procedures, and train client or engineering teams on AI-enabled DevOps pipeline automation.

**Nice to Have**

• Experience with GitHub Copilot extensibility or custom AI agents.

• Familiarity with vector databases and Azure AI Search for embedding-based workflows.

• Prior work building AI-powered DevOps dashboards or reporting tools.

• Experience with Kubernetes-native observability tools such as Prometheus, Grafana, or Datadog.

**Additional Job Information**

This is an offshore role that requires daily collaboration with U.S. stakeholders, including overlapping work hours to ensure effective partnership and meet business needs.

**Weekly Hours:**

40

**Time Type:**

Regular

**Location:**

IND:KA:Bangalore / Intl Tech Park, Navigator Bldg, Whitefield Road: Intl Tech Park, Navigator Bldg:Intl Tech Park, Navigator Bldg

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