Sr Site Reliability Engineer

Role Overview

We are seeking a Senior Site Reliability Engineer (Automation & Google Cloud Platform) to lead the design, scaling, and operational modernization of our cloud infrastructure ecosystem. In this role, you will be responsible for building robust automation frameworks, managing complex cloud configurations, and integrating modern AI/ML capabilities into our Site Reliability Engineering (SRE) operations.

As a senior technical leader, you will bridge hands-on engineering execution with high-level architectural advisory. You will drive self-healing infrastructure, design guardrail-driven workflows across existing CI/CD tools, and establish best practices for intelligent incident remediation and observability across Google Cloud Platform (Google Cloud Platform).

Key Responsibilities

• Automation Framework Engineering: Develop and maintain robust, scalable automation frameworks using Python to automate and manage the full lifecycle of complex cloud infrastructure.

• Infrastructure as Code (IaC): Design, build, and maintain enterprise Infrastructure as Code (IaC) environments using Terraform and Terragrunt to guarantee consistency, replicability, and compliance across multi-environment deployments.

• SRE Workflow & Tooling Integration: Engineer and deploy auditable, guardrail-driven continuous workflows integrated seamlessly with core SRE platforms, including JIRA, Git, and CI/CD pipelines.

• Google Cloud Platform AI/ML Solution Architecture: Architect and implement intelligent, cloud-native automation solutions on Google Cloud Platform to streamline system monitoring, alerting, and operational processes.

• Self-Healing Infrastructure: Leverage Google Cloud Platform AI services, predictive analytics, and automated orchestration to enable proactive incident remediation, dynamic resource scaling, and resilient self-healing operational workflows.

• Technical Advisory & Strategic Leadership: Advise client and internal engineering teams on Google Cloud Platform best practices, reliability engineering principles, and the integration of AI-driven automation into DevOps ecosystems.

Qualifications

• Expert Python Engineering: Expert-level proficiency in Python, specifically for engineering CLI tools, operational scripts, and scalable infrastructure automation.

• Infrastructure as Code Mastery: Extensive, proven experience designing and managing scalable cloud infrastructure using IaC tooling like Terraform and Terragrunt.

• Git & CI/CD Expertise: Deep expertise in Git version control (including complex branching strategies) alongside hands-on experience building and maintaining robust CI/CD pipelines.

• Deep Google Cloud Platform Expertise: Proven track record of designing, deploying, and managing enterprise-scale cloud architectures on Google Cloud Platform (Google Cloud Platform certification preferred).

• AI/ML Operations: Hands-on experience implementing AI-driven automation, Vertex AI, or ML pipelines to enhance system reliability, predictive capabilities, and operational efficiency.

• Configuration Management: Strong experience parsing, managing, and standardizing multi-format configuration data (e.g., YAML, INI, HCL) within automated workflows.

• AI-Ready System Design: Demonstrated ability to design automation procedures that are deterministic, enforce precise guardrails, and are structured for execution by AI agents or orchestration engines.

• Technical Leadership & Collaboration: Strong consultancy and leadership skills, with the ability to articulate complex technical strategies and align implementation details with business outcomes.