As I keep studying to improve at what I do, I keep asking myself this question and never seem to have a solid answer. Is seniority simply about years of experience? Or is it about expertise, autonomy, and the ability to design and deliver reliable, scalable systems while mentoring and guiding teams? The result was good, though with an interesting twist.
The way I conducted this quick survey was by using a generic prompt across the three most popular AI models at the time of this writing, which I will keep undisclosed. The goal was simply to examine the results and see whether they converge on a similar plan.
Prompt:
What does it mean to be a Senior Software Engineer (focused on backend)? You can discuss years of experience, programming languages they should know, key books, and any other arguments to provide a precise and concise summary.
✍🏼 Results
AI 1 - To be a Senior Backend Software Engineer means possessing a deep, independent expertise in designing, developing, and maintaining robust, scalable, and efficient server-side systems, typically backed by 5+ years of dedicated experience. This involves mastering at least one backend language (e.g., Python, Java, Go, Node.js), coupled with a strong command of databases (SQL/NoSQL), APIs (REST/gRPC), system architecture, distributed systems, and cloud platforms like AWS, Azure, or GCP, alongside proficiency in CI/CD. Beyond coding, it encompasses mentorship, solving complex technical challenges, driving strategic technical decisions, and contributing to the overall architectural vision. Essential reads like "Designing Data-Intensive Applications" and "Clean Code" encapsulate the theoretical and practical knowledge expected, ultimately positioning the senior engineer as a leader who transforms business requirements into reliable, performant, and maintainable backend solutions.
AI 2 - A Senior Software Engineer focused on backend development typically brings 5-8+ years of experience and represents a blend of deep technical expertise and leadership capabilities. They possess mastery of backend languages like Java, Python, Go, or C#, along with comprehensive knowledge of databases (both SQL and NoSQL), system design principles, API development, and cloud platforms such as AWS, Azure, or GCP. Beyond pure coding skills, they demonstrate system thinking by designing scalable and maintainable architectures, understanding distributed systems, microservices patterns, caching strategies, and performance optimization techniques. Their role extends into mentoring junior developers, leading technical decisions, conducting thorough code reviews, and driving architectural choices that impact entire product ecosystems. Essential reading includes "Designing Data-Intensive Applications" by Kleppmann, "System Design Interview" by Xu, and "Clean Architecture" by Martin. Most importantly, senior engineers translate business requirements into robust technical solutions while balancing technical debt against feature delivery, possessing strong debugging skills, DevOps knowledge including CI/CD and containerization, security awareness, and the ability to collaborate effectively across product and design teams to deliver meaningful business impact
AI3 - Being a Senior Software Engineer (backend) means having 5+ years of experience, technical autonomy, system design skills, and focus on delivering value. Strong in languages like Go, Java, or Python, databases (SQL/NoSQL), messaging, and scalable architectures. Familiar with Clean Code, Design Patterns, and DDD. Leads by example, reviews code, proposes robust solutions, anticipates issues, and drives impact with a strong sense of ownership.
Analysis and Thoughts
After reviewing the responses, I consolidated and summarized them into key points, as follows:
🧑🏽🏭 Experience
5+ years (typically 5-8+) of backend-focused professional experience
Technical autonomy and independence
📊 Technical Expertise
Mastery of one or more backend languages: Go, Java, Python, Node.js, C#
Deep knowledge of databases (SQL & NoSQL)
API development (REST, gRPC)
Strong understanding of system design, distributed systems, microservices
Familiar with caching strategies, messaging systems, performance optimization
☁️ Architecture & Cloud
Experience with scalable and maintainable architectures
Cloud platforms: AWS, Azure, GCP
Proficient in CI/CD, DevOps, containerization (e.g., Docker, Kubernetes)
👥 Leadership & Mentorship
Mentoring junior engineers
Leading technical decisions and architectural choices
Conducting thorough code reviews
👔 Soft Skills & Business Impact
Ability to translate business requirements into robust technical solutions
Balance technical debt vs. delivery
Collaborate effectively across teams (e.g., product, design)
📚 Essential Knowledge & Books
"Designing Data-Intensive Applications" by Martin Kleppmann
"Clean Code" by Robert C. Martin
"System Design Interview" by Alex Xu
Familiar with Design Patterns, DDD (Domain-Driven Design)
As expected, the responses were very good, and I agree with every single point — especially those related to backend engineering itself, such as cloud and architecture. However, for some reason, none of them mentioned AI as a tool or as part of the requirements. Was this omission intentional, or was my prompt not phrased correctly? I leave this question to you, the reader, and will provide an additional prompt to help explore the role of AI in this context.
▶️ Bonus prompt: What about AI and how it helps the engineer ?
While AI is incredibly powerful, it's crucial to remember that it augments, rather than replaces, the human engineer. Human intuition, creativity, ethical judgment, and the ability to understand nuanced user needs and business context remain irreplaceable. The most effective engineers in the AI era will be those who can leverage these tools effectively to amplify their own capabilities and tackle more challenging and impactful problems.
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