A software engineer designs, builds, tests and maintains software. Coding is part of the job, but the role is wider. Engineers also design APIs, model data, review code, control access and help run software after release.
The key skill is judgement. A feature must work when an API times out, a payment is retried or a user lacks permission. For a CTO, an engineer’s ability to handle those cases often matters more than another framework on a CV.
What does a software engineer do?
A software engineer turns a product need into software that works in production.
The work usually covers design, development, testing and maintenance. Current career guides from Indeed, Coursera and Intuit describe the role in similar terms.
The exact job depends on the product and team.
| Role | Main focus | Typical problem |
| Frontend | User interface | State, accessibility, browser performance |
| Backend | APIs and business logic | Transactions, data, authentication |
| Mobile | Mobile applications | Devices, offline behaviour, releases |
| Data | Data pipelines | Data quality, storage, processing |
| DevOps/cloud | Delivery and infrastructure | CI/CD, environments, monitoring |
| AI | AI-enabled features | Data, evaluation, permissions, fallbacks |
A senior engineer may spend less time writing new code and more time reviewing designs, finding risks and making architecture decisions.
The common goal is simple: make the product behave correctly under real conditions.
Good engineering starts before coding
A product request is rarely detailed enough to build safely.
Consider a FinTech requirement:
“Let a customer withdraw money.”
Before coding, the engineer needs answers. Who can make the withdrawal? Which balance is correct? Can two withdrawals run at once? What happens when the payment provider succeeds but the application never receives its response?
These questions shape the system.
One timeout can create two transactions
Consider this flow:
request → payment provider → payment succeeds → response
Now the response is lost:
request → payment succeeds → timeout → client retries
If the backend treats the retry as a new operation, it could create another transaction.
One common control is an idempotency key. The operation gets a unique identifier. A repeated request with the same identifier can be recognised instead of processed as new.
The exact implementation depends on the payment provider and system design.
The wider lesson is more useful: engineers need to design the failure path as well as the happy path.
Architecture is a series of tradeoffs
Software architecture defines how applications, services, databases and external systems work together.
More complexity does not mean better engineering.
A young SaaS product may work well as a modular monolith. Splitting the same application into many microservices adds deployments, network calls and new failure points.
Microservices can make sense when parts of the system need separate scaling, releases or team ownership.
The useful question is:
What problem does this architecture solve?
If the team cannot answer that clearly, the extra complexity may not be worth its cost.
APIs expose the hard parts of software
External APIs create boundaries that an engineering team cannot fully control.
A FinTech platform may connect to payment, banking, identity and accounting services. HealthTech software may depend on healthcare, insurer or identity systems.
Those services can time out. Rate limits can block calls. Responses can arrive late. An API can change.
The engineer must decide what happens next.
Fundree: financial data meets the Meta API
Code & Pepper’s work on Fundree shows the problem in a real product.
Fundree needed a central platform for managing advertising funds. Its backend is a TypeScript API built with NestJS and uses PostgreSQL. The customer-facing application uses Next.js and React. The platform also integrates with the Meta API.
The Meta integration can create advertising accounts, retrieve their status and update budgets. Fundree also has a separate back-office application for internal management.
Money created another engineering constraint.
Code & Pepper chose Dinero.js to handle monetary values. The library avoids the floating-point rounding problems that can appear when normal binary floating-point numbers are used for decimal money.
The Fundree FinOps engineering breakdown explains those architecture choices in more detail.
The lesson is small but important. When data represents money, the way a team stores and calculates that data becomes a product decision.
Testing should follow business risk
Testing effort should reflect the damage a defect could cause.
A unit test can check a fee calculation. An integration test can check whether a payment creates the right database record. An end-to-end test can check the full customer flow.
Those tests solve different problems.
A wrong payment amount deserves more attention than a minor visual defect.
Code & Pepper’s August 2026 guide to QA engineer interview questions makes the same distinction. It focuses on whether QA engineers can design a test strategy that finds meaningful defects before production, rather than simply produce test cases. The article was published on August 6, 2026.
When a product needs dedicated testing support, Code & Pepper’s quality assurance services add specialist QA work alongside development.
Security lives inside application logic
Security depends on everyday engineering decisions about permissions and data.
Consider this API request:
GET /accounts/123
Authentication can prove who sent the request.
It does not prove that the person can access account 123.
The backend must still check access to that record.
OWASP ranks Broken Access Control first in its 2025 Top 10. OWASP includes cases where a user accesses another person’s record by changing an identifier. It recommends enforcing access control in trusted server-side code or serverless APIs.
For FinTech, HealthTech and InsurTech products, auditability can add another requirement.
A system may need to record who changed a value, what changed and when the action happened. These requirements affect data models, permissions and logging from the start.
Production is still an engineering problem
Shipping code is not the end of the job.
Engineers need to know whether software works after release. Logs, metrics and alerts provide that feedback.
Infrastructure health alone is not enough.
A payment service can have normal CPU usage while failed transactions rise. A healthcare integration can stay online while a queue stops processing updates.
Useful monitoring should therefore include product behaviour as well as infrastructure health.
Code & Pepper’s August 2026 AWS DevOps guide covers continuous integration, continuous delivery, infrastructure as code and observability. It also explains the role of automated tests, repeatable environments, monitoring and rollback procedures.
This matters because deployment and production behaviour are part of the same engineering system.
Software engineer vs software developer
Software engineer and software developer are overlapping titles. Employers do not use them in one standard way.
Some companies use “engineer” for roles with wider system or architecture ownership. Others use both titles for similar work.
For a CTO, the job title matters less than the person’s scope.
Ask what the candidate has designed, shipped and supported. Code & Pepper’s guide to what a software developer does covers the development role from the product-delivery side.
The skills that matter to a CTO
A strong engineer needs more than knowledge of one programming language.
Four capabilities matter most.
Programming and data. Engineers need depth in their main stack and enough database knowledge to work safely with product data.
System design. Senior people should reason clearly about APIs, transactions, queues, service boundaries and failure modes.
Testing and debugging. Engineers need to reproduce failures, find the cause and stop the same defect from returning.
Communication. They should explain technical risk in terms a product leader can use.
For example:
“We can ship the payment flow sooner without asynchronous processing, but a provider timeout could leave the transaction state unclear. A queue takes more work now but gives us a controlled recovery path.”
That gives a CTO a decision to make. A list of frameworks does not.
AI changes the workflow, not ownership
AI tools can speed up parts of software development. They do not remove the need for engineering review.
An AI-generated API endpoint can compile and still expose the wrong customer’s data.
Someone must review permissions, tests, data handling and failure behaviour.
Code & Pepper’s AI development and integration services take that wider product view. The service covers architecture, data readiness, application development, APIs, permission models, deployment, monitoring and fallback paths around AI features.
The model is only one part of the product.
The engineering question remains: can the team verify and operate the whole system?
How much does a software engineer cost in 2026?
Robert Half’s current US benchmark ranges from $109,250 to $175,500, with a midpoint of $142,000. The figures vary by experience and skill level.
That is the salary. It is not the total cost of employing someone.
External development uses another pricing model. Clutch’s software development pricing guide, updated August 27, 2026, reports an average company rate of $25 to $49 per hour.
| Benchmark | Current figure |
| US software engineer benchmark | $109,250 to $175,500 |
| US midpoint | $142,000 |
| Software development company rate | $25 to $49/hour |
These numbers should not be compared as equivalent prices.
A permanent employee also creates recruitment, benefits, equipment and management costs. An external development company may supply several roles and a different delivery model.
For a CTO, the useful measure is the total cost of solving the engineering problem.
What is a realistic software delivery timeline?
Clutch’s verified software project reviews show a usual project timeline of about 13 months. The average reviewed project cost in the same dataset is $132,480.29.
Those figures are market benchmarks, not estimates for a specific product.
A focused change can take days or weeks. A large platform can take many months. A useful estimate depends on scope, integrations, data migration, security work and existing architecture.
External dependencies can also control the schedule.
Adding five developers will not make a third-party provider approve API access five times faster.
That is why good planning starts by finding the critical path, not by choosing a team size first.
CoverTree: architecture shaped by the product
Code & Pepper’s CoverTree project shows why architecture should follow product needs.
CoverTree needed to integrate with a third-party Policy Management as a Service provider. The backend also had requirements around security, reliability, scaling and infrastructure maintenance.
Code & Pepper chose AWS serverless architecture for the backend.
The frontend had a different need. Several applications had to share components and follow a consistent design. The team chose a monorepo, which keeps code for multiple projects in one repository.
The CoverTree case study connects those choices to an actual InsurTech product rather than presenting serverless or monorepos as universal answers.
That is the technical lesson: start with the constraint, then choose the architecture.
Hiring for judgement, not keywords
A senior engineering interview should test what a candidate does when the answer is unclear.
Consider this scenario:
“A payment provider completes a withdrawal, but your API times out before confirmation arrives. What should happen next?”
A strong candidate should ask about transaction state, provider behaviour, idempotency, reconciliation, retries and monitoring.
“Retry the request” is not enough.
For a senior product role, four areas give a useful signal:
| Area | What to test |
| Technical depth | Can the candidate work in the required stack? |
| System thinking | Can they find failure modes and explain tradeoffs? |
| Production ownership | Have they diagnosed real incidents? |
| Domain judgement | Do they understand the cost of failure? |
This tests engineering judgement rather than memory.
More engineers do not always mean faster delivery
Extra people help when engineering capacity is the real bottleneck.
If developers are waiting for requirements, another developer adds another person to the queue.
If releases depend on manual infrastructure work, DevOps expertise may have more value. If defects keep returning, QA or architecture may be the missing capability.
Smart Pension is a useful example of a genuine capacity problem.
Code & Pepper built two dedicated engineering teams with more than 40 specialists. The case study reports 20+ branch merges per day and nearly 100% test coverage for the project.
The lesson is not to add people by default.
It is to identify the bottleneck first.
When missing capacity or a specific skill really is the constraint, Code & Pepper’s software team augmentation service can add developers, testers, project managers and designers to an existing team. The client keeps the final candidate decision.
The decision that matters for a CTO
Good software engineering closes the gap between a product requirement and a system that works under real conditions.
The gap is different in every company.
Fundree needed careful financial data handling and external API integration. CoverTree needed architecture shaped by insurance workflows and third-party systems. Smart Pension needed more engineering capacity while keeping strict delivery and testing practices.
The next engineering investment should follow the same logic.
If unreliable APIs block releases, fix the integration layer. If releases are fragile, improve delivery and observability. If defects keep returning, strengthen QA. If the roadmap is sound but the team lacks capacity, add the missing engineering skills.
The commercial question is simple:
Which engineering constraint is stopping the product from shipping safely?
Solve that constraint before buying more development hours.
What does a software engineer do every day?
The work can include designing solutions, writing and reviewing code, testing changes, fixing defects and discussing requirements. Senior roles often include more architecture and production decisions.
Is software engineering mostly coding?
No. Coding is central to the job, but the role also includes design, testing, debugging and maintenance. The balance depends on the product and seniority.
What is the difference between a software engineer and a developer?
The titles overlap and employers use them differently. In practice, compare responsibilities, system ownership and production experience rather than relying on the title.
What programming languages do engineers use?
The language depends on the product. Common choices include JavaScript, TypeScript, Python, Java, C#, Go, C++, Swift and Kotlin.
Do engineers test their own code?
Yes. Engineers commonly test the components they build. QA specialists add wider test strategy, automation, exploratory testing and system-level validation.
How much does a software engineer earn in the US?
Robert Half’s current national benchmark is $109,250 to $175,500, with a midpoint of $142,000.
How much does external software development cost?
Clutch reports an average rate of $25 to $49 per hour for software development companies in its current pricing data. Actual project cost depends on scope, team, location and delivery model.
How long does a software project take?
Clutch’s verified review data reports a usual timeline of about 13 months across its software development dataset. That is a broad market benchmark, not a standard MVP or feature timeline.
Will AI replace software engineers?
AI can automate parts of coding and analysis. Engineers still need to define system behaviour, review output, test software, manage risk and own production results.