Lead Cloud Infrastructure Engineer

About the company

Egen is a fast-growing, entrepreneurial organization that works with a data-led approach. The team combines strong engineering talent with advanced platforms such as Google Cloud and Salesforce to help clients turn data and insights into action. The company values curiosity, continuous learning, and solving difficult problems with speed and effectiveness.

Role overview

This position is for an experienced Lead Cloud Infrastructure Engineer who enjoys designing and supporting complex cloud environments. The role requires a broad architectural mindset, with responsibility for building infrastructure that is scalable, secure, highly available, and performant. You will also mentor engineers, collaborate with clients, and help deliver practical technical solutions aligned to business needs.

Key responsibilities

• Architect and deliver secure, resilient, and scalable infrastructure solutions, with a primary focus on Google Cloud.
• Build and maintain infrastructure as code using Terraform so environments remain consistent, repeatable, and easy to manage at enterprise scale.
• Use Kubernetes deployment tooling such as Helm and Kustomize, along with GitOps platforms like ArgoCD, to manage containerized workloads.
• Create and improve CI/CD pipelines using tools such as GitHub, GitLab, Bitbucket, Cloud Build, and Harness, supporting rolling, canary, and blue/green releases.
• Maintain strong auditability and visibility into pipeline activity and state.
• Embed security controls, audit readiness, and compliance requirements into infrastructure design and operations.
• Coach, guide, and train engineering team members to strengthen technical capability.
• Work with clients to gather technical and business requirements and translate them into suitable solutions.
• Investigate and fix complex infrastructure problems.
• Take the lead in incident response, including troubleshooting, root cause analysis, triage, escalation, communication, and post-incident reviews.
• Track application and infrastructure reliability through monitoring and observability platforms.
• Define and manage SLIs, SLOs, error budgets, and alerting approaches to improve service reliability.

Candidate profile

The ideal applicant brings deep hands-on infrastructure engineering experience, especially in Google Cloud and Kubernetes environments. The role calls for someone who can design for scale, handle high-performance workloads, and work confidently across automation, deployment, reliability, and security topics. Strong communication, stakeholder management, mentoring ability, and incident leadership are essential.

Experience and qualifications

• At least 9 years of experience in infrastructure engineering or a closely related field.
• Strong exposure to Google Cloud (GCP).
• Proven track record of designing systems for scale, availability, and performance.
• Advanced knowledge of Terraform and infrastructure as code practices.
• Hands-on experience with Kubernetes and associated tools such as Helm, Kustomize, and ArgoCD.
• Good understanding of Git, branching strategies, CI/CD workflows, and deployment patterns.
• Working knowledge of security, audit, and compliance best practices.
• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication, with the ability to work with technical and non-technical stakeholders.
• Background in mentoring teams, building ownership, and encouraging self-organization.
• Experience managing client relationships and contributing to project planning.
• Solid incident management and major incident handling experience.
• Practical knowledge of observability, including logging, metrics, tracing, and distributed tracing concepts.
• Ability to define and manage SLIs, SLOs, and alerting strategies.

Preferred certifications and additional exposure

• Relevant certifications such as Kubernetes Certified Administrator or Google Cloud Certified Professional Cloud Architect are preferred.
• Software development experience with tools or languages such as Terraform and Python is beneficial.
• Exposure to machine learning infrastructure is an added advantage.

Eligibility

Any graduate can apply.