DevOps Engineer II

About Learneo & QuillBot: Learneo is a premier, internationally recognized educational technology pioneer, digital productivity innovator, and multi-brand SaaS platform leader on an absolute mission to supercharge learning and writing efficiency for everyone worldwide. Operating as a unified family of builder-driven businesses, Learneo attracts, integrates, and scales high-growth companies founded by visionary entrepreneurs, including Course Hero, CliffsNotes, LitCharts, Symbolab, Scribbr, and our industry-leading AI writing companion, QuillBot. Launched with a dedicated focus to help students and professionals strengthen their writing craft, QuillBot now empowers more than 56 million active global users to think clearly, communicate effectively, and produce high-quality work across every digital platform at the speed of thought. Backed by centralized enterprise administrative infrastructures, Learneo fosters an AI-forward, highly experimental engineering network. The organization provides cloud craftsmen with an uncompromised remote canvas to tackle large-scale distributed architecture challenges and advance open learning tech systems safely across global cloud fabrics.

Position Overview

We are seeking a highly analytical, systems-minded DevOps Engineer II to join our core centralized QuillBot Platform SRE group in a full-time remote capacity within India. Operating as a critical contributor within our distributed infrastructure cell, you will step up to claim individual strategic operational accountability for supporting the design, rapid deployment, and rigorous maintenance of our high-throughput, multi-region, and multi-cloud platform layers. Shifting completely away from manual system patching or routine virtual machine configuration, you will serve as a core technical anchor primarily managing our Google Cloud Platform (GCP) configurations, ensuring uncompromised system availability, low latency, and infinite scalability across all user-facing services. This position requires a cloud native professional with 3–6 years of DevOps history who maps containerized clusters fluidly, deploys declarative GitOps networks smoothly using ArgoCD, and optimizes high-scale server environments to seamlessly support heavy Machine Learning (ML) training and inference data pipelines.

Key Responsibilities

• Multi-Cloud Infrastructure Governance: Assist in the provisioning, optimization, and scaling of multi-region and multi-cloud server topologies, prioritizing resilient execution, safety, and performance constraints primarily inside Google Cloud Platform (GCP).
• Agentic AI Workflows Implementation: Design, build, and maintain sophisticated agentic AI workflows and internal automation networks, integrating large language models (LLMs), custom orchestration frameworks, backend APIs, and telemetry hooks to maximize team deployment velocity natively utilizing DevOps pipelines.
• Automated Pipeline Engineering: Partner peer-to-peer with application development squads to design, debug, and maintain secure continuous integration and continuous delivery tracks natively leveraging Python scripts and GitLab CI structures.
• Kubernetes Cluster Triage: Manage, monitor, and scale production-grade Google Kubernetes Engine (GKE) environments, ensuring clean cluster node provisioning, network access boundaries, and workload balancing.
• Declarative GitOps Delivery Management: Deploy and maintain infrastructure environments using automated GitOps workflows, ensuring declarative system synchronization directly using ArgoCD platforms.
• Infrastructure-as-Code Automation: Model and maintain complete version-controlled system architectures, writing clean, reusable blueprints natively using Terraform modules and Ansible playbooks.
• Reliability Auditing and Incident Response: Participate actively within the team’s on-call engineering rotation, contributing to root-cause analysis, production error tracking, and systemic environment troubleshooting to reinforce site reliability metrics.
• Runbook and Knowledge Curation: Author, structure, and systematically expand internal technical runbooks, disaster recovery steps, and system architecture diagrams to facilitate smooth onboarding and continuous team learning.

Required Skills & Qualifications

• 3 to 6 years of verified professional history running advanced DevOps engineering, site reliability operations (SRE), cloud systems architecture, automated release management, or full-stack pipeline consulting.
• Deep, authoritative technical command of cloud-native infrastructure patterns, Linux/Unix operating system administration, basic TCP/IP networking, IAM roles, and VPC configuration parameters.
• Expert-tier background building automated multi-region deployment paths, containerizing distributed services, and coding declarative orchestration blocks natively utilizing DevOps toolsets (specifically Terraform, GKE, and ArgoCD).
• Practical operational familiarity writing automated infrastructure scripts, API endpoints, or cleaning tracks natively leveraging Python, Bash, or Go programming setups.
• Hands-on production history auditing system telemetry, tracking container alerts, and monitoring error states using tools like Prometheus, Grafana, ELK stack, or GCP Cloud Monitoring.
• Outstanding verbal and written communication traits in business-fluent English, ensuring absolute clarity when specifying architectural requirements for both distributed engineering groups and AI development agents.
• Location Context: Position open exclusively to qualified cloud engineers based permanently and resident within **India** to execute platform operations under a virtual-first 100% remote layout.

Preferred Strategic Indicators (Nice to Have)

• Prior commercial infrastructure programming or SRE history operating within a high-volume consumer SaaS company, artificial intelligence product lab, automated text-processing startup, or global EdTech technology platform.
• Hands-on architectural exposure orchestrating multi-cloud deployments that cross-connect GCP systems with alternative major providers (such as AWS or Microsoft Azure).
• Familiarity with distributed machine learning training architectures, microservice mesh networks, and international traffic routing optimization.
• An outcome-driven personal philosophy rooted in continuous learning, an intentional mindset that questions automated assumptions, and a passion for making the path from inspiration to execution more accessible.

What We Offer

• The exceptional professional canvas to directly direct, shape, and code-engineer the multi-cloud infrastructure models and agentic AI pipelines power-routing writing tools for 56 million worldwide QuillBot users.
• Highly competitive, capability-benchmarked full-time baseline salary packages supplemented by a performance-linked corporate annual bonus structure.
• Profound work-from-home remote parameters providing an elite virtual-first environment, complete scheduling trust, and zero physical geographic office commuting friction across India.
• Immediate eligibility to enroll in comprehensive protection packages, including premium medical coverage alongside life and accidental insurance structures.
• Access to excellent personal lifestyle calibration benefits, featuring flexible vacation parameters and diverse leaves of absence (including menstrual, special, and flexible leave options).
• Continuous skill acceleration pathways through dedicated education and developmental cost reimbursements, professional workshops, and structured mentorship alongside elite senior platform specialists.
• Generous workplace allowances, explicitly featuring home internet/mobile billing subsidies, initial WFH setups, and premium full-tier access to the complete QuillBot software suite.