Quick overview
Job description
Essential Responsibilities:
- Lead design, modernization, and governance of enterprise cloud platforms on GCP.
- Establish reference architectures, IaC standards (Terraform), and reusable patterns.
- Define multi-region, HA, and disaster recovery architectures; lead legacy-to-cloud migrations.
- Own FinOps, cost optimization, and cloud operational efficiency.
- Build and operate large-scale GKE environments (Standard and Autopilot).
- Deliver core platform capabilities: service mesh, API gateway, secrets, container security, networking, identity federation, and multi-region deployment.
- Standardize Helm-based deployments and drive resilience through self-healing automation.
- Define enterprise CI/CD standards and fully automated pipelines across Dev, QA, Stage, and Production.
- Implement release governance, progressive deployment, guardrails, and rollback.
- Improve engineering productivity through automation and self-service platform capabilities.
- Own reliability for critical customer-facing applications: SLIs, SLOs, error budgets, and availability targets.
- Lead incident response and executive communications during critical events, root cause analysis, post-incident reviews, and automated remediation.
- Champion resilience testing and a reliability-first engineering culture.
- Own observability strategy across infrastructure, applications, databases, APIs, and AI services.
- Build unified dashboards, proactive monitoring, anomaly detection, and executive operational metrics.
- Partner with Security, Architecture, and Risk teams on secure-by-design platforms.
- Implement IAM governance, workload identity, secrets management, encryption, WAF, and network segmentation.
- Embed DevSecOps in CI/CD; support SOC2, security assessments, and regulatory audits.
- Lead infrastructure and operations for AI-powered and agentic products.
- Enable secure deployment and governance of generative AI, agent platforms, MCP servers, RAG/vector workloads, and AI APIs.
- Establish AI observability, lifecycle management, and enterprise-ready deployment patterns.
- Partner with Data Engineering on reliability, performance, backup/DR, and operational support for core data services (PostgreSQL, Cloud SQL, search, messaging, and pipelines).
- Mentor DevOps, SRE, cloud, and software engineers; set standards and lead architecture reviews.
Skills and/or Certifications Needed:
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Bachelor’s degree in Computer Science, Engineering or related field
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8+ years in Cloud Engineering, DevOps, Platform Engineering or SRE.
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5+ years leading major enterprise platform initiatives.
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Proven experience operating large-scale production systems on GCP and/or AWS.
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Expert-level Terraform; strong Kubernetes (GKE), Docker, Helm, cloud networking, API gateways, and cloud security.
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Enterprise CI/CD pipeline experience (Harness, GitHub Actions, Jenkins, or GitLab).
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Strong automation skills (Python, Bash, or similar).
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Experience with PostgreSQL, cloud databases, distributed systems, production incidents, and RCA.
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Strong understanding of security, compliance, and governance frameworks.
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GCP Professional Cloud Architect / DevOps Engineer, AWS Solutions Architect Professional, or Terraform Associate qualification is preferred.
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Experience with observability tooling (e.g., Splunk), GitOps, and AI platform technologies (LangChain/LangGraph, MCP, vector databases, AI governance) is preferred.
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Background in regulated or enterprise SaaS environments is an advantage.
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Show an ownership mindset in everything you do; be a problem solver, be curious and be inspired to take action, be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
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Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
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Where applicable, fluency in English and languages relevant to the working market.
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