DevOps career advancement is often a matter of seizing the right opportunities at the right time. For one engineer, that meant leveraging DevOps skills to become a CTO in their late twenties—proof that a strong DevOps career path can lead to executive leadership. Yet according to a recent MIT report, 95% of organizations are getting zero return on their AI investments. This gap creates a significant opportunity for DevOps leaders who can bridge technical execution with strategic outcomes.
This article outlines five concrete actions you can start taking now to accelerate your own career. Whether you’re targeting a CTO from DevOps transition or simply want to increase your impact, these steps are designed to help you stand out in a rapidly evolving field.
1. Lead AI Initiatives That Deliver Business Value
You are perfectly positioned to close the AI ROI gap by leading practical, production-focused AI projects. Many organizations struggle to move beyond AI hype, but DevOps engineers have the hands-on experience to turn ideas into working systems. The key is to define clear business outcomes from the start — whether that means faster deployments, fewer incidents, or more reliable releases. Treat AI as a collaborator, not a black box. Rukmini Reddy, SVP of engineering at PagerDuty, advises this approach, emphasizing that leadership itself is a craft you can develop. Start with small, measurable AI experiments that integrate into your existing workflows rather than trying to overhaul everything at once.
How to Pick the Right AI Initiative
Focus on areas where generative AI for operations can reduce toil, such as automating incident response summaries or improving log analysis. Ensure you have proper AI governance in place to maintain reliability and security. By delivering tangible wins, you demonstrate how AI in DevOps directly supports business goals — a powerful move for your DevOps career advancement. Each successful project builds your reputation as someone who can bridge technical execution and strategic value.
2. Establish Standards for Generative AI Tools
Without standards, generative AI tools can introduce security risks and inconsistent practices across your software development lifecycle. DevOps engineers are in a unique position to set the rules and define guardrails for how these tools are used. This is a practical way to steer AI adoption in a safe, efficient direction. By creating a shared set of best practices for using AI—from planning and coding to testing and monitoring—you ensure that every team member follows the same guidelines. That consistency reduces errors, makes audits clearer, and strengthens your overall development process.
Focus on three key areas: AI code generation, prompt engineering, and model selection. For AI code generation, implement mandatory AI code review for any code produced by an AI assistant. This prevents potentially flawed or insecure code from slipping into production. For prompt engineering, develop prompt engineering standards and share templates that help your team get reliable, repeatable results from generative models. For model selection, create an approved list of tools so that no one accidentally uses an unsanctioned model. These steps build a robust AI tool governance framework. When you lead this effort, you demonstrate initiative and strategic thinking—both valuable for your DevOps career advancement.
3. Build a Platform or Practice That Teams Actually Want to Use
Once you have a handle on AI governance, turn your attention to something more tangible: creating tools and workflows that developers genuinely enjoy using. The most influential DevOps engineers build internal platforms that make life easier for their colleagues, earning both recognition and trust along the way. Start with the fundamentals—automate your builds, script your deployments, standardize your infrastructure configurations, and monitor system performance. These are core DevOps tasks you likely already do. The real shift comes when you move beyond just automating for yourself and start designing a self-service infrastructure that empowers other teams to work independently.
Think of it as building an internal developer platform that abstracts away complexity. Instead of developers waiting for you to provision a server or fix a pipeline, they can self-serve through a simple interface or API. This dramatically improves the developer experience and reduces friction across the organization. To know if you are succeeding, measure adoption rates and developer satisfaction. A platform that teams love to use demonstrates leadership naturally—you are not just fixing problems, you are preventing them at scale. Developing a platform or practice that teams actually want to use is one of the most effective moves for DevOps career advancement, because it shows you understand both technology and people.
4. Transition from Automation to Strategic Business Skills
Once automation frees up your time, it’s tempting to keep perfecting your scripts. But the real opportunity lies elsewhere. Shift your focus from building pipelines to understanding customers, products, and revenue. This is where DevOps career advancement accelerates, because you move from being a technical executor to a strategic contributor. Automation already enabled development teams to focus on building and testing applications while operations managed infrastructure. That means you have room to grow beyond the terminal.
Use that freed time to learn customer needs, partner with product managers, and understand marketing and sales operations. The author was able to focus on higher-level tasks such as these, which directly improved how teams delivered value. To build business acumen for engineers, set aside a few hours each week for cross-functional collaboration. Sit in on a product review, shadow a sales call, or ask a marketing colleague about their biggest challenge. This tech to business transition doesn’t require leaving your role—it just requires a deliberate shift in where you spend your attention. The result is a more rounded skill set that makes you indispensable to both engineering and the business.
5. Demonstrate Leadership and Get Noticed for C-Level Opportunities
That shift in attention can also catch the eye of leadership. Visibility with the C-suite comes from solving business problems, not just technical ones. Treat leadership as a craft—seek mentorship, communicate your impact in business terms, and volunteer for strategic projects. For example, the author stepped into the CTO role when the previous CTO left, something that was unusual in the 1990s for someone in their late twenties. Being ready when opportunity arises is key to DevOps career advancement.
Signs You Are Ready for a C-Level Role include the ability to drive cross-team initiatives, communicate ROI, and manage stakeholders effectively. These skills build executive visibility and show you can handle broader responsibilities. Rukmini Reddy, SVP of engineering at PagerDuty, advises treating AI as a collaborator and leadership as a craft. By demonstrating stakeholder management and CTO readiness, you position yourself for the next step—whether that’s a promotion or a lateral move into a more strategic role.
Frequently Asked Questions
How do I establish standards for generative AI tools in my team?
Start by defining acceptable use cases and security requirements for AI tools. Create a simple evaluation checklist covering data privacy, output reliability, and team productivity. Involve your team in periodic reviews to keep standards practical and up-to-date. This approach supports devops career advancement by showing leadership in governance.
What does a platform that teams love look like, and how do I build one?
A loved platform is self-service, reliable, and reduces friction for developers. Build it by identifying the most common manual tasks your team faces and automating them first. Focus on clear documentation and fast feedback loops. This shift toward platform engineering is a key step in devops career advancement.
How can I transition from focusing on automation to higher-level business tasks?
Begin by mapping your current automation work to business outcomes like faster deployments or lower error rates. Volunteer for cross-functional projects that connect technical decisions to revenue or customer satisfaction. Develop your communication skills to translate technical results into business value. This transition directly fuels devops career advancement.
