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McCain Foods

DevSecOps Engineer, IE&O

Posted 5 Hours Ago
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In-Office
Gurugram, Haryana
Senior level
In-Office
Gurugram, Haryana
Senior level
Designs, secures, operates, and automates enterprise cloud infrastructure and DevSecOps platforms across Azure and Google Cloud. Responsibilities include CI/CD and GitOps, infrastructure as code, Kubernetes, security controls, observability, governance, incident response, reliability engineering, toolchain integration, and developer enablement. The role also applies generative AI responsibly to infrastructure automation while maintaining security, compliance, human oversight, and cost controls.
The summary above was generated by AI
Position Title:DevSecOps Engineer, IE&O
Position Type: Regular - Full-Time
Requisition ID: 45078
Role Overview
The DevSecOps Engineer is a senior hands-on engineering role within the Enterprise Infrastructure Platform Engineering team. The role designs, implements, secures, and operates resilient cloud infrastructure and enterprise DevSecOps platforms, with a strong focus on automation, developer enablement, governance, reliability, and measurable delivery outcomes.
Working primarily with Microsoft Azure and also Google Cloud, the engineer partners with platform architects, security, application, data, and AI teams to embed security, quality, observability, and change controls throughout the software delivery lifecycle. The role also advances responsible use of generative and agentic AI in infrastructure-as-code and engineering workflows, supported by appropriate guardrails, human oversight, and FinOps discipline.
Success in this role means: secure-by-design platforms, reliable automated delivery, faster developer flow, auditable change, and reduced operational toil.
Key Responsibilities
Platform Engineering & Reliability: Design, implement, and monitor secure, fault-tolerant, highly available cloud infrastructure and DevSecOps platform services.
CI/CD & Release Engineering: Establish and continuously improve build, test, release, and deployment frameworks that support scalable delivery, traceability, auditability, and repeatability.
DevSecOps Adoption: Drive adoption of DevSecOps and cloud platform capabilities across application, data, and AI engineering teams through reusable patterns, enablement, and technical guidance.
Security by Design: Embed SAST, DAST, IAST, software composition analysis, secrets management, policy enforcement, and security quality gates into CI/CD pipelines.
Infrastructure as Code: Build and maintain modular, tested, and governed infrastructure automation using Terraform, Ansible, and related tooling.
GitOps & Kubernetes: Implement GitOps-based delivery and lifecycle management for container platforms using technologies such as Kubernetes, AKS, GKE, Argo CD, Flux CD, Helm, Docker, and Podman.
Toolchain Availability: Engineer and operate reliable services supporting source control, artifact management, containerization, continuous integration, release management, change management, and developer workflows.
Automated Governance: Integrate automated change-management controls, approvals, evidence capture, policy-as-code, and promotion controls across development-to-production pipelines.
Observability & Self-Healing: Integrate metrics, logs, traces, event analytics, and automated remediation to improve service health, troubleshooting, performance, and resilience.
Performance & Operations: Lead technical analysis, optimization, incident response, problem resolution, upgrade planning, operational readiness, and lifecycle management for DevOps infrastructure.
Cross-Functional Architecture: Translate development, security, operations, reliability, and compliance requirements into implementable platform designs and engineering standards.
AI-Assisted Engineering: Apply generative and agentic AI to accelerate infrastructure engineering and automation while maintaining human oversight, security guardrails, governance, and cost accountability.
Documentation & Enablement: Produce clear technical documentation, reference architectures, standards, runbooks, and reusable implementation guidance; coach teams on engineering best practices.
Automation Culture: Identify repetitive manual processes and replace them with secure, supportable, observable automation.
Required Skills and Experience
Core Experience
10+ years of relevant experience in DevSecOps, platform engineering, cloud engineering, task automation, or GitOps.
Hands-on engineering experience designing and operating enterprise-scale CI/CD, cloud infrastructure, container platforms, and automation frameworks.
Strong programming and scripting capability using Python, Bash, PowerShell, Groovy, Java, C#, C++, or comparable languages.
Proven operational discipline across incident response, problem management, performance analysis, upgrade execution, high availability, and technical documentation.
Strong communication and collaboration skills with the ability to work effectively across architecture, security, infrastructure, application, data, and AI teams.
Technical Capabilities Required
Capability Area
Expected Experience
Cloud Platforms
Microsoft Azure (Must); Google Cloud Platform (Nice to have).
Source Control & CI/CD
GitHub, GitHub Actions, Azure DevOps, or equivalent enterprise platforms.
Infrastructure as Code & Configuration
Terraform, Terratest, Ansible, Puppet, Chef, Salt, or equivalent tools.
Containers & Orchestration
Kubernetes, AKS, GKE, kubectl, Helm, Docker, Podman, or comparable technologies.
GitOps & Continuous Delivery
Argo CD, Flux CD, or equivalent GitOps tooling.
Application & Supply-Chain Security
SonarQube, Snyk, Akido, Chaingaurd, SAST, DAST, IAST, software composition analysis, dependency scanning, secrets scanning, and quality gates.
Artifact & Package Management
JFrog Artifactory or equivalent artifact repositories.
Observability
Grafana, Prometheus, Loki, or equivalent monitoring, logging, and analytics platforms.
ITSM & Work Management
ServiceNow, Jira, automated change integration, and auditable delivery workflows. Handson Experience of integrating DevOps tools chain and ServiceNow and Jira Integration
Testing & Service Virtualization
Selenium, Tosca, automated functional/performance/security testing, and service virtualization tools.
Linux & Networking
Ubuntu, Debian, Alpine, RHEL; TCP/IP, DNS, HTTP/S, SSL/TLS, SMTP, FTP, and cloud networking fundamentals.
AI-Enabled Engineering
GitHub Copilot, Claude Code, or comparable AI coding and engineering assistants, used within defined governance and security controls.
Qualifications
Bachelor's degree in computer science, engineering, information technology, or a related discipline; equivalent practical experience will also be considered.
Relevant public cloud certification in Microsoft Azure or Google Cloud is required.
DevOps, DevSecOps, Kubernetes, or CNCF certification is preferred.
Experience with Agile and DevOps delivery methods and with planning, estimation, and delivery in a fast-paced enterprise environment.
Demonstrated learning agility with the ability to evaluate and adopt emerging technologies responsibly.
Preferred Attributes
  • Systems thinker who balances developer experience, security, reliability, governance, and cost.
  • Self-starter who can operate with appropriate autonomy while maintaining strong stakeholder alignment.
  • Pragmatic engineer who favors standards, reusable products, automation, and measurable outcomes over one-off solutions.
  • Curious and adaptable, with a commitment to continuous learning and responsible adoption of AI-enabled engineering practices.

Key Outcomes
  • Secure delivery: Security and compliance controls are consistently embedded and evidenced within delivery pipelines.
  • Reliable platforms: DevSecOps services meet defined availability, performance, recovery, and support expectations.
  • Faster flow: Standardized automation reduces manual effort and enables repeatable, lower-risk releases.
  • Developer enablement: Product teams can adopt approved cloud and DevSecOps capabilities through clear, reusable patterns.
  • Operational excellence: Observability, incident learning, self-healing, and continuous improvement reduce recurring issues and operational toil.
  • Responsible AI adoption: AI-assisted engineering improves productivity without compromising security, governance, quality, or cost control.

McCain Foods is an equal opportunity employer. As a global family-owned company, we strive to be the employer of choice in the diverse communities around the world in which we live and work. We recognize that inclusion drives our creativity, resilience, and success and makes our business stronger. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, age, veteran status, disability, or any other protected characteristic under applicable law.
McCain is an accessible employer. If you require an accommodation throughout the recruitment process (including alternate formats of materials or accessible meeting rooms), please let us know and we will work with you to find appropriate solutions.
Your privacy is important to us. By submitting personal data or information to us, you agree this will be handled in accordance with McCain's Global Privacy Policy and Global Employee Privacy Policy , as applicable. McCain leverages AI in the hiring process, though all final decisions are made by humans. You can understand our approach to AI and how your personal information is being handled here .
Job Family: Information Technology
Location(s): IN - India : Haryana : Gurgaon
Company: McCain Foods(India) P Ltd

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