Senior DevOps Engineer

Qodo (formerly Codium); Northern (KY); Hybrid; USD 160,000 - 180,000; Full time

Benefits offered by this job

Stock options

Medical, dental & vision plans

401(k) plan

Commuter Allowance

Job summary

Qodo is seeking a Senior DevOps Engineer (Cloud-Prem) to own enterprise deployments of a Kubernetes-based platform in customer-managed clouds (AWS, GCP, Azure). You will debug, script, and automate for scalable, reliable operations while collaborating with enterprise teams to onboard US-based clients.

You will codify best practices using Terraform and Helm, manage PostgreSQL/Redis databases, and ensure secure, performant environments across multiple customer stacks.

Qualifications

• 5+ Years in DevOps / Infrastructure in a product-driven B2B SaaS, DevOps tooling, or developer platform context.
• Autonomous & autodidactic mindset with the ability to make technical decisions independently.
• Client-facing deployment, onboarding, or Field DevOps experience and strong communication with client engineers.
• Location: You must be located in Central Time Zone USA.

Responsibilities

• Own Enterprise Deployments: install, configure, and upgrade Qodo's Kubernetes-based stack within customer-managed cloud environments (AWS, GCP, Azure).
• Debug & Reverse-Engineer: real-time troubleshooting, diagnostics, and custom Python/Bash scripts to overcome constraints.
• Bridge Engineering & Customers: serve as technical counterpart to enterprise teams during onboarding to minimize time-zone delays for US clients.
• Build for Scale & Self-Document: codify best practices into IaC modules (Terraform, Helm) and create internal knowledge for repeatable onboarding procedures.
• Drive Reliability: ensure optimal performance of core infra components (PostgreSQL, Redis, container networking, storage) within client stacks.

Skills

Kubernetes

Containers

Cloud platforms (AWS/GCP/Azure)

Python

Bash

PostgreSQL

Redis

Linux networking

Git

On-call / incident response

Tools

Terraform

Helm

Docker

Kubernetes

Job description

At Qodo, we're building an AI Code Review platform that helps developers move fast, ship with confidence, and elevate code quality across the SDLC through deep, scalable codebase understanding.

As a Senior DevOps Engineer (Cloud-Prem) at Qodo, you will take total ownership of our enterprise deployments, running and integrating our Kubernetes-based platform directly inside customer-managed cloud environments (AWS, GCP, Azure). This is a highly autonomous, ground-level role where you'll navigate complex, unfamiliar systems, solve zero-day installation challenges, and make high-stakes client deployments succeed from day one.

In this role you will

• Own Enterprise Deployments: Take end-to-end ownership of installing, configuring, and upgrading Qodo's Kubernetes-based stack within customer-managed cloud environments (AWS, GCP, Azure)
• Debug & Reverse-Engineer: Real-time troubleshooting on environments you are seeing for the first time. You'll pull diagnostics, identify root causes, and write custom Python/Bash scripts to overcome network, access, or platform constraints
• Bridge Engineering & Customers: Serve as a high-touch technical counterpart to enterprise engineering teams during onboardings, eliminating time-zone delays for US-based clients (working alongside Solutions Engineering as needed)
• Build for Scale & Self-Document: Codify best practices into IaC modules (Terraform, Helm) and create a structured internal knowledge base to turn "one-off" fixes into repeatable, automated onboarding procedures
• Drive Reliability: Ensure optimal performance and health of core infrastructure components (PostgreSQL, Redis, container networking, and storage) within isolated client stacks

Requirements

• 5+ Years in DevOps / Infrastructure: Proven track record in product-driven B2B SaaS, DevOps tooling, or developer platform companies
• Autonomous & Autodidactic: Extreme ownership mentality - comfortable navigating ambiguity, making technical decisions independently, and driving projects forward without waiting for top-down direction
• Client-Facing DNA: Hands-on experience in customer-facing deployment, technical onboarding, or Field DevOps contexts. You communicate clearly and build trust with client engineers under pressure
• Location: You must be located in Central Time Zone USA

Technical Core

• Deep Kubernetes & Containers: Expert-level, hands-on experience running, troubleshooting, and tuning complex production Kubernetes clusters and Docker containers
• Cloud & IaC Mastery: Proficiency with Terraform and Helm across major public clouds (AWS, GCP, Azure), particularly within customer VPC/tenant boundaries
• Networking & Infrastructure Services: Solid understanding of Linux networking, IAM/security policies, storage drivers, and database infrastructure management (PostgreSQL, Redis)
• Diagnostic Scripting: Strong capability in Python or Bash to write quick diagnostic tools, automation scripts, and deployment fixes

Nice to Have

• Software development background (building tools, services, or SDKs)
• Experience with AI/ML developer tools or enterprise developer platforms
• Prior experience being the first remote hire in a region or building early-stage operational playbooks

For this position at Qodo, we offer:

• The expected salary range for this role is $160,000 - $180,000 per year. Actual compensation will depend on various factors, including experience, skills, and location
• All Qodo team members are also eligible for stock options, reflecting our belief in shared ownership and long-term growth
• Comprehensive medical, dental, and vision plans for you and your dependents, with company contributions toward your premiums
• 401(k) plan
• Commuter Allowance: We support flexible work, and for those who travel to the office two or more times a week, Qodo provides a commuter allowance to cover part of your travel costs

Are you legally authorized to work in the United States?

Yes

No

Will you now or in the future require visa sponsorship to work in the United States?

Yes

No

This role requires being based in Central time Zone USA, working completely remote. Are you able to work in a fully remote model, while located in CDT?