What Software Engineers Do, Courses, Degrees & Requirements
By
Liz Fujiwara
•
Jan 16, 2026
Software engineers impact almost everything you use, from booking flights to streaming shows to interacting with AI, but for founders and AI team leads, the role can feel opaque. In 2026, top engineers do far more than write code. They turn ideas into MVPs in weeks, build recommendation engines that boost conversion, integrate LLMs into production, manage cloud infrastructure, and architect systems that scale to millions of users. Modern software engineering involves product collaboration, architecture decisions, security, observability, and direct accountability for user impact across web, mobile, cloud, and AI systems. Hiring has become more complex because you need engineers who understand the full development lifecycle, can make build versus buy decisions, and adapt as tech stacks evolve. This article covers what engineers do daily, the education and alternative paths that prepare them, and how Fonzi helps companies hire elite AI and software engineers more efficiently.
Key Takeaways
Software engineers design, build, test, deploy, and maintain software systems that power products, internal tools, and AI-driven applications across modern companies, and their education paths include bachelor’s degrees, intensive bootcamps, or self-taught routes with certifications like AWS, Kubernetes, or CompTIA.
The software development lifecycle spans requirements gathering, system design, coding, testing, deployment, and ongoing maintenance, with engineers increasingly owning the full stack from frontend to cloud infrastructure.
Fonzi is an AI-native hiring platform that helps startups and enterprises hire elite AI and software engineers in under three weeks with consistent evaluations, preserving candidate experience while giving founders and hiring managers higher confidence in technical hiring decisions.
What Software Engineers Do Day to Day
For hiring managers who aren’t deeply technical, understanding what software engineers actually do helps evaluate candidates and set realistic expectations.
Requirements and Planning
Engineers start by understanding what needs to be built. They work with product managers to translate business goals into technical requirements, create specifications, and estimate timelines. This process management ensures the team builds the right thing before writing code.
Software Design and Architecture
Before coding, engineers decide how the system should be structured. This includes choosing between monolithic and microservices architectures, designing APIs, selecting databases, and planning for scalability and reliability. Senior engineers often lead design discussions and make critical build versus buy decisions.
Implementation and Coding
Writing code remains central to the role. Engineers program in languages like Python, Java, JavaScript, Go, C#, or TypeScript depending on the project. They implement features, fix bugs, and refactor existing code for better performance or maintainability. Version control with Git and participation in code reviews are daily activities.
Testing and Quality Assurance
Engineers own the quality of their work. They write unit tests, integration tests, and end-to-end tests. They integrate automated testing into CI/CD pipelines so tests run on every commit. Modern practices expect engineers to “shift left” on software testing rather than relying solely on separate QA teams.
Deployment and Operations
Engineers deploy applications to staging and production environments using Docker, Kubernetes, and cloud platforms like AWS, Azure, or GCP. They monitor system performance, respond to incidents, and participate in on-call rotations. This combination of development and operations reflects the DevOps approach.
Maintenance and Continuous Improvement
Software doesn’t end at launch. Engineers troubleshoot production issues, patch security vulnerabilities, upgrade dependencies, and reduce technical debt. Maintaining software systems over years is a significant part of the job that often gets overlooked in hiring conversations.
Collaboration and Communication
Engineers spend substantial time in meetings such as standups, sprint planning, design reviews, and retrospectives. They work with designers on user interface decisions, consult with security specialists, and present technical tradeoffs to stakeholders. Strong communication skills are essential.
Specialization Areas
Engineers often specialize within this broad scope:
Backend engineers focus on server-side logic, APIs, and databases
Frontend engineers build user interfaces using React, Vue, or Angular
Full-stack engineers work across both layers
Mobile engineers specialize in iOS or Android development
DevOps and platform engineers automate infrastructure and deployments
AI and ML engineers build data pipelines, train models, and productionize machine learning systems
Senior engineers also mentor juniors, lead architecture decisions, and align technical work with business objectives.
Types of Software Engineers and Roles You Can Hire
When building a team, understanding the different types of software engineers helps you match candidates to your actual needs.
Backend Engineers
Backend engineers work with Java, Go, C#, Python, or Node.js to build APIs, microservices, and data processing systems. They design and implement the logic that powers your application, handle database management, and ensure systems scale reliably. Backend expertise is critical for complex business logic or high-traffic products.
Frontend Engineers
Frontend engineers own the user experience. They use React, Vue, Angular, and TypeScript to build responsive web applications. They focus on performance, accessibility, and turning design mockups into production-ready interfaces. Strong frontend engineers understand web development deeply and can optimize for real-world user behavior.
Full-Stack Engineers
Full-stack engineers ship features end-to-end, from database to UI. They are valuable for early-stage startups where small teams need flexibility. A full-stack engineer can build your MVP, iterate quickly, and wear multiple hats as you scale.
Data and AI/ML Engineers
These engineers build data pipelines, integrate LLMs, and productionize models for recommendations, fraud detection, or internal copilots. They bridge research and production, working with Python, ML frameworks like PyTorch and TensorFlow, and data management tools. Demand for these skills has surged as AI becomes central to more products.
DevOps and Platform Engineers
DevOps engineers automate deployments, manage cloud costs, and ensure uptime. They work with infrastructure as code such as Terraform or CloudFormation, container orchestration like Kubernetes, and observability tools including Prometheus, Grafana, Datadog, and Sentry. Platform engineers build internal tools that make other engineers more productive.
Security Engineers
Security engineers focus on software security, threat modeling, secure coding practices, and compliance. They ensure systems meet regulatory requirements and protect user data from breaches.
Mobile Engineers
Mobile engineers specialize in iOS with Swift, Android with Kotlin, or cross-platform frameworks like React Native or Flutter. They handle mobile-specific constraints including battery life, connectivity, and platform design guidelines.
Fonzi focuses on elite AI and software engineers across these categories, with particular strength in AI-native roles like LLM application engineers, ML platform engineers, and infrastructure-minded full-stack developers.
Courses, Degrees, and Educational Paths for Software Engineers
There are multiple valid entry paths into a software engineering career, each with different trade-offs. Understanding these paths helps hiring managers evaluate candidates and helps aspiring engineers plan their development.
Traditional 4-Year Bachelor’s Degree
The classic path is a bachelor’s degree in computer science or a software engineering major from an accredited university. These programs typically cover:
Computer programming fundamentals
Data structures and algorithms
Operating systems and computer architecture
Databases and data modeling
Computer networks and distributed systems
Software engineering principles and project management
Discrete mathematics and linear algebra
Many programs now include coursework in machine learning, cloud computing, and web development to keep pace with industry needs. A software engineering bachelor’s degree provides deep theoretical foundations that help engineers reason about complex problems and build systems that scale.
Online Degree Programs
Accredited online software engineering programs follow similar curricula to on-campus degrees while offering flexibility for working professionals or remote learners. Look for programs with strong faculty, accreditation, and coverage of modern topics like cloud platforms and AI.
Intensive Bootcamps
Coding bootcamps (typically 3-9 months) focus on practical skills that get graduates job-ready quickly. Programs cover full-stack web development, Python for data, mobile application development, and increasingly, LLM application building. Bootcamps excel at teaching modern frameworks and tools but may provide less depth in computer science fundamentals. They can cost $8,000-$25,000 and offer accelerated entry into the field.
Self-Taught Paths
Self-taught engineers combine MOOCs, open courseware, and hands-on portfolio projects. This path requires discipline but shows motivation and independent learning ability, valued in fast-changing fields. Many engineers start this way, using GitHub and open-source contributions to build credibility.
Typical Software Engineering Curriculum and Skills
For hiring managers, understanding what should be in an engineer’s educational background helps you ask the right interview questions and identify gaps. Key foundational subjects include:
Algorithms and data structures: Essential for efficiency and scalability, including choosing the right data structure and analyzing time and space complexity.
Computer architecture and operating systems: Understanding low-level computer operations enables better performance optimization and debugging.
Networking and distributed systems: Critical for web services, microservices, and cloud-native applications.
Databases and data modeling: SQL, NoSQL, schema design, indexing, and query optimization are daily tools.
Software engineering practices: Version control, code reviews, design patterns, testing strategies, and documentation.
Object-oriented programming: Most enterprise codebases use OOP principles, making this foundational.
Systems engineering principles: Thinking holistically about component interactions and system evolution.
Modern curricula often include AI-related coursework: introduction to machine learning, deep learning, natural language processing, and LLM systems. Strong communication, product sense, and critical thinking are emphasized and are key evaluation points when hiring.
Certifications and Continuing Education
While a degree provides foundations, professional certifications signal up-to-date skills in fast-moving areas like cloud and AI. Common certifications include:
Cloud and DevOps
AWS Certified Solutions Architect or AWS Certified Developer
Google Professional Cloud Architect
Azure Administrator Associate
Kubernetes certifications (CKA, CKAD)
Software Delivery
CompTIA Project+ for project management basics
Scrum Master certifications for agile development teams
Terraform and other infrastructure-as-code credentials
AI and Data
DeepLearning.AI specializations
NVIDIA Deep Learning certifications
Google Professional ML Engineer
OpenAI and Databricks credentials
Many employers view certifications as “nice to have” rather than required, prioritizing real-world impact. For candidates from non-traditional backgrounds, certifications can demonstrate competency. Fonzi’s talent pool includes engineers who combine strong fundamentals with recent specialized learning, particularly in generative AI and cloud-native tools.
Requirements to Become a Software Engineer (With and Without a Degree)
Whether following a traditional academic path or not, certain baseline skills matter for employability: proficiency in a major programming language, understanding of algorithms and data structures, familiarity with Git and development tools, basic database knowledge, experience with a cloud platform, and understanding of software testing and deployment.
Entry-level candidates should have 1-2 production-grade projects, internship or open-source experience, familiarity with version control, and a basic understanding of systems design and networking. AI engineering and senior roles require experience with distributed systems, production ML, measurable business impact, deep domain expertise, and leadership or mentoring experience.
Non-degree paths succeed by building portfolios on GitHub, contributing to open source, demonstrating problem-solving, earning relevant certifications, and gaining freelance or contract experience. The IT industry increasingly values skills and impact over credentials, though some specialized roles still favor formal education.
Fonzi focuses on demonstrated skill, portfolio quality, real-world scenarios, and structured assessments, allowing fair evaluation regardless of degree, bootcamp, or self-taught background.
How Fonzi Helps You Hire Elite AI and Software Engineers
Traditional technical hiring is slow, inconsistent, and draining. Manual sourcing, unstructured interviews, and ad hoc assessments often take 2-4 months, create noisy signals, and lead to candidate drop-off, which can cost you top AI talent.
Fonzi makes technical hiring fast, consistent, and scalable for AI-related roles. It sources or vets candidates for the skills and experience you need, runs structured role-specific assessments covering coding, system design, AI/ML knowledge, and communication, and matches hires within about three weeks.
Fonzi supports roles across LLM application engineering, ML, data platforms, infrastructure-focused backend, and full-stack product engineering, while providing a positive candidate experience with clear expectations, timely feedback, and fair evaluations that let candidates showcase their strengths.
Why Fonzi Is Different From Traditional Recruiters and Job Boards
If you’ve used agencies, LinkedIn, or generic job boards, you know the limitations:
Resume screening based on keywords rather than demonstrated ability
Inconsistent take-home tests that candidates hate
Interviewers who focus on different things, making comparison impossible
Slow feedback loops that frustrate candidates
Fonzi takes a different approach:
Skill-Based Assessments
Rather than keyword matching, Fonzi evaluates actual capabilities through structured challenges aligned to the role.
Consistency at Scale
For enterprises hiring across multiple teams and locations, Fonzi provides a consistent evaluation bar. You get comparable data whether you’re hiring in San Francisco, London, or Bangalore.
Startup-Friendly Rigor
Early-stage companies often lack the resources to build sophisticated interview processes. Fonzi lets you “borrow” enterprise-grade evaluation rigor without building an in-house hiring pipeline from scratch.
Strong Candidate Brand
Fonzi maintains thoughtful communication, clear timelines, and role-aligned challenges. Candidates feel respected, which protects your employer brand in competitive talent markets.
Example Roles and Hiring Scenarios Fonzi Supports
Early-Stage AI Startup
A seed-stage company needs their first AI engineer to build an LLM-based copilot into their SaaS product with deep Python expertise, vector database experience, and prompt engineering skills. Fonzi identifies candidates who can own the project end-to-end and integrate it into production.
Scale-Up Re-platforming
A growth-stage company needs 10-20 backend and data engineers to migrate their monolith to event-driven microservices on AWS or GCP within 6-12 months. Fonzi provides a steady pipeline of vetted engineers who understand distributed systems and can hit the ground running.
Enterprise ML Platform Build-Out
A large organization is adding specialized ML platform engineers to integrate model observability, feature stores, and MLOps practices across multiple business units. Fonzi tailors assessments to cover ML infrastructure, data engineering, and cross-functional collaboration skills.
Domain-Specific Hiring
Whether you need engineers with financial aid system experience, electrical and computer engineering backgrounds, or expertise in software reverse engineering, Fonzi adapts matching criteria to your tech stack, seniority, and domain requirements.
Comparison of Paths: Degrees, Bootcamps, and Self-Taught (With Table)
When evaluating candidates, hiring managers often encounter engineers from very different training backgrounds. Understanding the trade-offs helps you ask better interview questions and identify gaps to probe.
Below is a comparison of the three main paths into software engineering:
Path | Typical Duration | Indicative Cost (USD) | Strengths | Common Gaps |
4-Year Bachelor's Degree | 4 years | $40,000 - $160,000 | Deep CS fundamentals, algorithms, theory, broad career flexibility | May lag on modern tools, AI, cloud; less practical project experience |
Intensive Bootcamp | 3 - 9 months | $8,000 - $25,000 | Job-ready practical skills, modern frameworks, fast entry | Shallower fundamentals, may struggle with system design or complex backend |
Self-Taught | Variable (1-3 years typical) | $0 - $5,000 | High self-motivation, flexible learning, strong portfolio focus | Gaps in CS theory, networking, may lack structured knowledge |
What This Means for Hiring
When interviewing degree holders, focus on practical project experience and familiarity with modern tools. For bootcamp graduates, assess understanding beyond the frameworks they learned. For self-taught candidates, evaluate CS fundamentals and their ability to learn new concepts systematically.
Fonzi evaluates actual skills and outcomes rather than over-indexing on education, making it easier to compare candidates from diverse backgrounds and surface top talent fairly.
Conclusion
Software engineers build and maintain the systems that power modern businesses, from apps to cloud infrastructure to AI products. Candidates come from degrees, bootcamps, or self-taught paths, which makes fair evaluation challenging.
Fonzi helps you hire faster and at scale: most hires close in three weeks, structured assessments provide consistent comparisons, and the process works for your first AI hire or your 10,000th while giving candidates a respectful, transparent experience.
If you’re planning AI or software engineering hires in the next 6-12 months, book a demo or start a pilot with Fonzi to streamline and strengthen your technical hiring.
