Senior DevOps Engineer

Job Overview

We are seeking a Senior DevOps Engineer to act as a technical pillar of our platform team. In this role, you will transition from simply maintaining infrastructure to actively designing, building, and scaling it. You will own the lifecycle of several existing and brand-new infrastructure projects, driving architectural decisions, upgrading our CI/CD pipelines, and integrating modern AI-driven workflows and autonomous agents into our platform ecosystem.

As a Senior DevOps Engineer you will work with a high degree of autonomy. While you will collaborate with Staff and Principal Engineers on advanced architectural patterns, you are expected to independently lead projects from conception to production. Your work will directly impact our system's reliability, developer velocity, operational autonomy, and overall engineering efficiency.

Key Responsibilities

System Design & Technical Execution

• Build & Redesign: Lead the creation of new infrastructure projects and drive the comprehensive redesign of aging legacy systems to modern, cloud-native standards

• Infrastructure as Code (IaC): Architect, write, test, and manage robust IaC templates using Terraform across multi-cloud environments

• Process Modernization: Identify bottlenecks in our engineering workflows and design, document, and implement entirely new processes to optimize our DevOps maturity

• Advanced Automation & Agentic Workflows: Build robust automation frameworks using Python (primary language) and AI agents to automate routine support, maintenance tasks, log analysis, and incident triage, eliminating manual operational toil

Autonomy, Consultation & Leadership

• Independent Execution: Take full ownership of projects. You will be responsible for planning, executing, and deploying your initiatives with minimal daily oversight

• Collaborative Design Reviews: Partner with Staff and Senior Staff Engineers to review architectural designs, ensuring alignment with company standards, advanced patterns, and AI/agent capabilities

• Documentation & Shared Knowledge Champion: Author clear system architecture diagrams and runbooks. Build and maintain centralized AI prompt/skill libraries and tooling to elevate team capabilities

Security, Support & Mentorship

• Vulnerability Management & AI Guardrails: Take a proactive role in triaging complex security issues, defining IAM policies, and establishing safety guardrails and access controls for cloud environments and autonomous AI agents

• Automated Support & Developer Advocacy: Serve as a technical advisor for dev teams, building AI-assisted support tools (e.g., automated troubleshooting agents) to drive developer self-service

Qualifications

Technical Expertise:

• Cloud Architecture: Deep production experience with GCP (Google Cloud Platform) and/or AWS (Amazon Web Services)-ideally both

• Infrastructure as Code: Advanced proficiency in Terraform, including writing modular, reusable, and secure configurations

• CI/CD Pipelines: Deep expertise in constructing and optimizing enterprise-grade pipelines, with a strong preference for GitLab (and/or GitHub)

• Scripting, Software Engineering & AI Integration: Strong software engineering fundamentals in Python, paired with practical experience leveraging AI, LLM tooling, or agentic frameworks (e.g., Google ADK, LangChain, or custom tool-calling agents) for operational automation

• Containers & Orchestration: Production-grade experience managing Kubernetes (K8s) clusters, helm charts, and containerized microservices using docker images

• Serverless & Microservices: Hands-on experience architecting and deploying solutions utilizing AWS Lambdas, GCP Cloud Run, and container automation frameworks

Professional Competencies:

• High Ownership & Accountability: You understand that your technical choices carry a broad blast radius where downtime or misconfigurations result in significant business delays. You design with high availability, self-healing, guardrails, and rollback strategies in mind

• Architectural & AI Pragmatism: You know when to build a custom solution, when to leverage existing cloud-native tools, and how to evaluate AI solutions to solve real operational problems rather than chasing hype

• Strong Communicator: Ability to explain highly technical, low-level cloud concepts clearly to stakeholders, product developers, and business partners