Monthly Archives: August 2026

Hiring Senior Engineers Beyond Coding Interviews

Hiring Senior Engineers

For a long time, I strongly believed in coding interviews, especially when hiring senior engineers. I wanted to know whether candidates could write clean code, solve problems, understand algorithms and data structures, and make sound technical decisions.

I still believe those skills matter.

However, after spending years building engineering teams and hiring senior engineers, my thinking has evolved. I have learned that coding ability is only one part of what makes someone a great senior engineer.

One of the most important lessons came from candidates who had strong technical skills but struggled to demonstrate system thinking. They could solve the problem in front of them, but when the discussion moved toward architecture, ownership, trade-offs, business impact, and what happens beyond their own piece of code, the gap became visible.

That changed the way I think about senior engineering hiring.

The question is no longer simply, “Can this person write good code?”

The more important question is:

“What kind of impact will this person have on the engineering organization?”

What to Look for When Hiring Senior Engineers

Let me be clear: I have not stopped believing in coding rounds.A senior engineer should have strong technical fundamentals. They should be able to write maintainable code, debug difficult problems, understand their technology stack, review other engineers’ work, and make sound technical decisions.

Technical competence is not optional.

But I have started looking at coding ability as the foundation rather than the complete definition of seniority.

As engineers become more senior, their responsibilities expand beyond implementation. They are expected to understand the larger system, make decisions under uncertainty, work with product and business teams, identify risks, mentor other engineers, and take ownership when something goes wrong.

That is where a traditional coding interview starts to become insufficient.

The Challenge of Hiring Senior Engineers

A typical engineering interview often follows a familiar pattern: coding round, technical discussion, system design, and finally a managerial or HR discussion.

There is nothing inherently wrong with this structure. The problem is how we interpret the results.

It is easy to use coding performance as a proxy for overall engineering capability. If someone solves difficult problems quickly and communicates their solution well, we naturally assume they will perform well in a senior role.

But senior engineering is rarely about solving a clearly defined problem with all the necessary information available.

Real engineering is messy.

Requirements change. Production systems fail. Customers behave differently than expected. Legacy systems have constraints. Teams disagree about technical decisions. Business priorities change halfway through implementation.

A senior engineer needs to operate effectively in that environment.

That requires more than coding skill.

Hiring Senior Engineers for Ownership

Over time, this has changed the way I approach hiring senior engineers. The biggest change in my thinking has been around ownership. A task-oriented engineer thinks, “I completed my task.”

A senior engineer should think, “I own the outcome.” There is a significant difference between the two. This is one of the biggest lessons I have learned while hiring senior engineers.

Imagine a production issue affecting customers. A task-oriented mindset might focus on determining which service or team is responsible for the problem. An ownership mindset starts somewhere else: the system is having an issue, customers are affected, and we need to understand what is happening and get it resolved. Ownership doesn’t mean that one engineer personally fixes everything. It means they take responsibility for moving the problem toward a resolution.

That is one of the strongest signals of seniority I look for today.

What Engineering Ownership Looks Like

Ownership starts with understanding outcomes rather than simply completing requirements.

A senior engineer should want to understand why something is being built, who will use it, what problem it solves, and what success looks like. They should be willing to challenge assumptions when necessary rather than blindly implementing whatever is written in a ticket.

Ownership also extends to quality. Quality is not something that belongs only to the QA team. Senior engineers should care about reliability, security, performance, maintainability, testing, observability, and operational readiness. If something they built creates repeated problems in production, completing the original ticket shouldn’t be considered the end of their responsibility.

The same applies to technical debt. Every engineering organization accumulates technical debt. The problem isn’t having technical debt; the problem is ignoring its impact. I look for engineers who can identify technical debt, explain the business and technical consequences, and propose a practical way to address it.

There is a big difference between saying, “This code is bad,” and saying, “This design will become a bottleneck as our usage grows. Here is the risk, here are the alternatives, and here is how I would improve it without disrupting current delivery.”

System Thinking in Senior Engineer Hiring

One of the biggest lessons I’ve learned from senior engineering interviews is that local optimization is not enough. An engineer might design an excellent component, but how does that component interact with the rest of the system? This is particularly important when hiring senior engineers, because the role demands a much broader view of the technology landscape.

Does it affect other services? Does it introduce database constraints? What happens to performance as usage grows? How will it be monitored? How will it be deployed? What happens when a dependency fails? How will another team maintain it six months from now?

These questions reveal whether someone is thinking about a component or thinking about a system. When I discuss architecture with senior candidates, I am not looking only for a particular architecture or technology choice. I am interested in how they arrive at the decision.

During architecture discussions, I pay attention to how candidates approach the problem. I look for people who ask clarifying questions, identify trade-offs, consider failure scenarios, and think about operational complexity. I also want to understand whether they consider cost, scalability, and the impact their decisions may have on other teams.

There isn’t always one correct answer. What matters is whether the engineer can reason through the problem.

The Questions I Ask Have Changed

Earlier in my career, I focused heavily on questions such as, “Write an algorithm to solve this problem.” I still use those questions when appropriate. But for senior engineers, I now spend more time asking about systems they have actually owned.

I might ask them to describe a system they were responsible for and then keep going deeper.

I usually start by asking why the system was designed that way and what alternatives were considered. From there, I want to understand what went wrong during implementation and what the engineer would change if they were making the decision today. I also ask how they measured success and what they learned once the system went into production.

These conversations often reveal much more than a theoretical architecture exercise. They show how someone behaves when they have real responsibility. These conversations often reveal much more than a theoretical architecture exercise.

They show how someone behaves when they have real responsibility.

I Look for the “Why”

One of my favorite ways to understand how a senior engineer thinks is to keep asking one simple question: why?

I want to understand the reasoning behind their technical decisions. Why was a particular database chosen? What made microservices a better fit than a simpler architecture? What problem did caching solve? Why was synchronous communication preferred? What was the thinking behind introducing a particular abstraction?

The conversation becomes even more interesting when we discuss decisions that involve trade-offs. Perhaps the team knowingly accepted some technical debt, or perhaps a simpler solution was rejected because it created problems elsewhere.

There isn’t necessarily a right answer to these questions. That is precisely why they are useful. I am not trying to determine whether a candidate would make the same decision I would make. I want to understand whether they can evaluate alternatives, recognize trade-offs, and explain the reasoning behind their choices.

A strong senior engineer doesn’t need to agree with me. They need to be able to explain why they made the decision and demonstrate that they understand its consequences.

Communication Is an Engineering Skill

Another lesson I have learned is that communication is not simply a “soft skill” that sits outside engineering. For senior engineers, communication is part of the engineering job.

Senior engineers work across product, business, QA, DevOps, security, architecture, and other engineering teams. They need to explain technical complexity to people who may not have the same technical background.

A senior engineer should be able to explain the available options, describe the trade-offs, recommend a direction, communicate the risks, and make the next steps clear.

That ability creates leverage. Technical knowledge that cannot be communicated effectively often remains isolated with one person. Good communication turns that knowledge into something the entire organization can use.

I Look for Engineers Who Multiply Others

Another strong indicator of seniority is the impact an engineer has on the people around them.

Technical leadership isn’t always about being the person with the deepest knowledge in the room. It is often about helping others become better engineers. I look for people who mentor teammates, give thoughtful feedback during code reviews, share knowledge, and help establish practices that make the entire team more effective.

A senior engineer should also be willing to invest time in less experienced engineers. Helping someone understand a difficult concept, guiding them through a design decision, or giving them the confidence to solve a problem independently can have a much greater long-term impact than solving the problem yourself.

The best senior engineers don’t become bottlenecks that everyone depends on. Instead, they create more capable engineers around them.

That is what I mean by multiplying others.

Individual contribution creates output. Engineering leadership creates leverage. And as engineers become more senior, that leverage becomes one of the most valuable things they can bring to an organization.

Seniority Is About Leverage

This is probably the biggest lesson I have taken from hiring and working with senior engineers. A junior engineer can create value by completing tasks. A mid-level engineer can independently solve problems.

A senior engineer should create leverage.

That leverage can come from better architecture, better engineering practices, better systems, better documentation, better automation, better technical decisions, and better mentoring.

The code they personally write is only one part of their contribution.

As engineers become more senior, I expect their impact to extend beyond their own repository, service, or sprint.

How I Think About Senior Engineer Evaluation

Today, when evaluating a senior engineer, I think about five dimensions: technical depth, system thinking, ownership, decision-making, and engineering impact. Technical depth tells me whether they can handle difficult engineering problems.

System thinking tells me whether they understand how individual decisions affect the broader product and architecture. Ownership tells me whether they take responsibility for outcomes rather than simply completing assigned work. Decision-making tells me whether they can evaluate trade-offs and make pragmatic choices under uncertainty.

Engineering impact tells me whether they make the systems and people around them better. Coding remains an important part of this evaluation. But it is one dimension of a much larger picture.

The Question I Ultimately Want Answered

After a senior engineering interview, there is one question I increasingly ask myself:

If I give this person a difficult engineering problem with ambiguity, will they wait for instructions, or will they take ownership and drive it toward an outcome?

That distinction matters because real engineering rarely looks like an interview problem. Production doesn’t give you a clean problem statement. Customers don’t provide algorithm constraints. Legacy systems don’t come with perfect architecture diagrams. Incidents don’t happen at convenient times. Business requirements change.

Senior engineers need to be comfortable operating in that ambiguity.

Hiring for the Engineer You Need Tomorrow

One of the biggest mistakes I try to avoid when hiring senior engineers is hiring only for today’s problems. When hiring a senior engineer, I want to understand what the organization will need from that person six months or a year from now.

I’m not only asking, “Can this person solve the problems we have today?”

I’m asking:

“Can this person help us solve problems we haven’t encountered yet?”

That requires technical depth, but it also requires curiosity, ownership, system thinking, communication, and the ability to make others better.

My Biggest Lesson From Hiring Senior Engineers

I still believe coding rounds have an important place in the hiring process. Strong technical fundamentals remain essential, and I continue to challenge senior engineers on their ability to solve difficult engineering problems.

What has changed is how I interpret those results.

A strong coding performance tells me that someone can solve a technical problem. It doesn’t necessarily tell me whether they can own a system, navigate ambiguity, make sound architectural decisions, or create impact beyond their individual contribution.

Over time, I have learned not to confuse coding ability with engineering maturity.

Some of the strongest senior engineers aren’t necessarily the people who write the most code. They are the people who make the right problems visible, take ownership when things go wrong, make thoughtful technical decisions, build systems that other engineers can work with, and raise the capability of the people around them.

That is what I now look for when hiring senior engineers.

At senior levels, I am not hiring someone simply to write code. I am hiring someone to own outcomes, solve problems, and raise the engineering capability of the organization.

From Code Chaos to an Enterprise-Grade CI/CD Platform: How I Standardized Engineering Delivery Across the Organization

Enterprise CI/CD Platform: Standardizing Engineering Delivery with Jenkins, Nexus & Kubernetes
Enterprise CI/CD Platform: Standardizing Engineering Delivery with Jenkins, Nexus & Kubernetes

Software delivery has evolved significantly over the last decade. Yet, many engineering organizations still struggle with inconsistent deployment processes, fragmented tooling, and dependency management issues that slow down development and increase operational risk.

When I took ownership of engineering delivery, I quickly realised that the challenge wasn’t simply the absence of CI/CD. The organisation had capable engineers, good products, and ambitious goals-but every team followed a slightly different way of building, packaging, and deploying software.

Different repositories had different build scripts.
Some applications were deployed manually.
Docker images were stored inconsistently.
Frontend teams downloaded packages directly from npm.
Python projects depended on public PyPI repositories.
Every deployment felt like its own unique process.

As engineering teams grow, these inconsistencies become technical debt.

Instead of solving deployment issues project by project, I decided to build Enterprise CI/CD Platform that every development team could use consistently. The objective wasn’t just automation. It was standardisation and governance. It was creating a software delivery platform that engineers could trust.

The Problem with Growing Engineering Teams

As organisations scale, delivery complexity increases faster than application complexity.
One team introduces a shared UI library. Another creates utility functions. Someone publishes a Docker image. Another team copies code instead of reusing it. Soon every project looks different. This creates several common challenges:

  • Manual deployments prone to human error
  • Different build processes across projects
  • Repeated code across repositories
  • Public dependency risks
  • Inconsistent versioning
  • Lack of deployment traceability
  • Slow onboarding for new developers
  • Difficult rollback during production incidents
  • No central governance for reusable components

These problems aren’t caused by poor engineers. They are symptoms of a platform that hasn’t evolved with the organisation.

Looking Beyond CI/CD

Many organisations believe adopting Jenkins, GitHub Actions, or Azure DevOps automatically means they’ve implemented CI/CD. In reality, these tools are only automation engines. A mature engineering platform goes much further.

It should answer questions like:

  • Where are application artifacts stored?
  • How are shared libraries managed?
  • Who owns reusable packages?
  • How do teams consume internal components?
  • How are deployments standardised?
  • How do we secure our software supply chain?
  • How do we make onboarding effortless?

Once we started asking these questions, it became clear that what we needed wasn’t another build server. We needed an internal engineering platform.

Enterprise CI/CD Platform Architecture

The delivery platform was designed around a simple philosophy. Every application should follow the same journey from source code to production. The architecture consisted of four primary components:

Azure DevOps

  • Source control
  • Pull requests
  • Branch policies
  • Sprint management
  • Work item tracking

Jenkins

  • Pipeline orchestration
  • Build automation
  • Test execution
  • Artifact creation

Sonatype Nexus Repository

  • Docker Registry
  • npm Registry
  • PyPI Registry
  • Versioned artifacts
  • Dependency caching

Kubernetes

  • Automated deployments
  • Rolling updates
  • Self-healing infrastructure
  • Container orchestration

This architecture established a single, repeatable software delivery pipeline that every project could adopt.

Azure DevOps as the Single Source of Truth

Everything begins with source code. We standardised repository structures, enforced pull request workflows, and introduced branch policies to improve code quality before builds even started. Every change became traceable. Deployment could be linked back to a work item. Every release had complete visibility. This eliminated ambiguity around what had changed and why.

Jenkins: Automating Every Build

Jenkins became the automation engine that transformed source code into deployable software. Rather than creating unique pipelines for every project, we established reusable pipeline templates that followed the same lifecycle:

  • Checkout source code
  • Install dependencies
  • Execute unit tests
  • Perform static analysis
  • Build the application
  • Build Docker image
  • Tag using semantic versioning
  • Publish artifacts
  • Trigger deployment

Because pipelines were defined as code, every application inherited the same engineering standards. Developers no longer had to remember deployment steps. The platform handled them automatically.

Nexus Repository: The Heart of Engineering Standardisation

This was arguably the most transformative part of the platform. Many teams use Nexus purely as a Docker registry. We expanded its role into a central engineering asset repository. Instead of downloading everything directly from the internet, our teams consumed approved, version-controlled packages from internal repositories. This significantly improved consistency, reliability, and governance.

Docker Registry: Trusted Container Images

Every build produced a versioned Docker image. Instead of building containers directly on deployment servers, Jenkins published immutable images into Nexus. This provided several benefits:

  • Central image repository
  • Consistent deployments
  • Easy rollback
  • Complete version history
  • Controlled access
  • Faster deployments

Deployments became predictable because every environment pulled the exact same container image. No surprises. No environment-specific builds.

npm Registry: Encouraging Reusable Frontend Engineering

One of the biggest improvements was introducing an internal npm registry. As frontend applications matured, multiple teams began solving the same problems repeatedly. Rather than copying code between repositories, we converted shared functionality into reusable packages.

Examples included:

  • Shared UI component library
  • Configuration framework
  • API client SDK
  • Authentication helpers
  • Common utilities
  • Design system components

Developers simply installed internal packages like any other dependency.
Versioning became controlled. Updates became intentional. Shared components evolved independently without affecting every project immediately. This dramatically reduced duplicate code while promoting engineering consistency across frontend applications.

PyPI Registry: Standardising Backend Development

The same philosophy was applied to Python services. Instead of copying helper modules between repositories, we published reusable Python packages into our internal PyPI registry. These packages included:

  • Authentication libraries
  • Logging framework
  • AI helper modules
  • Prompt management utilities
  • Database connectors
  • Common integrations
  • Shared middleware

Each package had proper versioning, ownership, and release management.
Developers focused on solving business problems rather than rewriting infrastructure code.

Why Internal Package Registries Matter

Many organisations underestimate the importance of private package repositories.
They deliver far more than convenience. They establish engineering discipline.

Benefits include:

  • Approved dependencies
  • Faster builds through caching
  • Better security
  • Reduced internet dependency
  • Controlled package versions
  • Central ownership
  • Easier auditing
  • Better governance

Most importantly, they encourage engineers to think in terms of reusable platforms instead of isolated projects.

Kubernetes Completed the Automation Story

Once artifacts were published, deployments became straightforward. Applications followed a consistent deployment workflow:

  • Source Code
  • Build
  • Unit Tests
  • Docker Image
  • Nexus Repository
  • Kubernetes Deployment
  • Health Checks
  • Rolling Updates
  • Application Available

Every release followed the same process. The deployment mechanism was no longer dependent on individual engineers. It became part of the platform itself.

Improving Security Through Standardisation

Modern DevOps is also about securing the software supply chain.
By centralising artifact management, we gained several security advantages:

  • Controlled package approvals
  • Private Docker images
  • Internal npm packages
  • Internal Python packages
  • Version traceability
  • Credential management
  • Immutable release artifacts
  • Reduced exposure to public dependency risks

Security became an integrated part of software delivery rather than an afterthought.

Developer Experience Improved Dramatically

One of the biggest wins wasn’t faster deployments. It was a better experience for developers. New engineers no longer spent days configuring environments. Projects followed the same structure. Dependencies came from trusted internal repositories.
Pipelines behaved consistently. Deployment steps were predictable. Developers could spend more time writing software and less time understanding infrastructure. That consistency improves productivity in ways that are difficult to measure but impossible to ignore.

The Business Impact of Enterprise CI/CD Platform

Technology leaders often focus on tools. Business leaders focus on outcomes. The platform delivered measurable improvements across the engineering organisation.

BeforeAfter
Manual deploymentsFully automated delivery
Different pipelinesStandardised CI/CD
Public dependenciesInternal package ecosystem
Code duplicationReusable libraries
Environment inconsistenciesImmutable artifacts
Difficult rollbackVersion-controlled releases
Slow onboardingFaster developer productivity
Limited governanceCentral engineering standards

Looking back, the achievement was not automating deployments. It was changing the way engineering teams worked together. As engineering leaders, our responsibility isn’t simply to choose the right tools. It’s to build Enterprise CI/CD Platform that enable our teams to deliver exceptional software with confidence, every single day.