APIs Your Team Can Ship On Every Week
A backend usually does not fail all at once. Endpoints get slower, deploys get scarier, tests get skipped, and one day nobody wants to touch the code. I build new APIs and fix existing ones in Python, with Django and FastAPI, so they handle real load, have tests you trust and can be released without a war room. I have done this as the sole backend owner of three Django systems and on platforms serving millions of records.
What Problems I Solve
Slow Endpoints
Find what is actually slow, usually queries, N+1 access or missing caching, and fix it with measurements before and after.
New APIs and Services
REST APIs designed from the contract out: OpenAPI spec, validation at the edge, versioning and clear errors that client teams can build against.
No Tests, Scary Changes
Bring an untested codebase back under test so refactors and releases stop being a gamble. I have taken suites from near zero to 80%+ coverage.
Monolith Decomposition
Split out the parts of a monolith that need to scale or change on their own, one service at a time, with no big-bang rewrite.
Data Integrity Under Load
Idempotent writes, transactions and validation so concurrent traffic and retries do not create duplicates or half-written records.
Load You Have Not Tested
Load tests that simulate real concurrency before a launch, so you find the breaking point on a staging environment instead of in production.
Value I Deliver
Faster Releases
CI/CD that makes a release routine. At OneTrust the pipelines I designed cut release cycle time by 60%, with multi-environment deploys in under 30 minutes.
Tests You Trust
Coverage on the code that matters, fast enough to run on every pull request, so a green build means something.
Correct Data
Schema validation, idempotent writes and transactional rollback, so a failure leaves the data clean and a retry is safe.
Documented Contracts
OpenAPI specs and examples that frontend and partner teams can use without asking the backend team every time.
Visible Behavior
Metrics, traces and alerts on every service, so problems show up on a dashboard before they show up in support tickets.
Easier Onboarding
Tooling that runs in a container on the first day. At SecurityScorecard, containerizing the support tools cut engineer onboarding from hours to under 60 minutes.
Real-World Implementations
Compliance Data APIs on Kubernetes
Challenge
OneTrust serves 14,000+ enterprise customers. After the Convercent acquisition, compliance records had to be ingested concurrently and at scale, where a duplicate or a half-written record is a compliance problem for the customer.
Solution
- Django REST endpoints deployed on Kubernetes for concurrent ingestion
- Idempotent writes, schema validation and transactional rollback across millions of records
- Phased validation across DEV, QA1, QA2 and PROD before each release
- Jira-triggered CI/CD pipelines with full auditability
- Audited three legacy services and brought their test coverage from near zero to 80%+
Results
The migration finished with zero data loss and zero production incidents, and the engineering standards I wrote were adopted team-wide. Read the full case study
Technologies Used
Sole Backend Owner of Three Django Systems
Challenge
Three Django systems behind a security-critical product, one backend owner, weekly feature work, and test suites that had been abandoned. A major platform refactor was waiting on those tests.
Solution
- Restored the abandoned test suites across all three repositories, from 0% to production-grade coverage
- Kept shipping features every week while the suites came back
- Containerized the internal support tooling with Docker
Results
The restored tests unblocked the platform refactor, and onboarding a new engineer went from hours to under 60 minutes. See all case studies
Technologies Used
Load Testing a Real-Time Banking Platform
Challenge
Caixa Bank needed to know how its platform behaved under heavy concurrent WebSocket traffic from operators and clients at the same time.
Solution
- Built a distributed load-testing framework running on AWS
- Simulated 30,000 concurrent operators and 100,000 virtual clients over WebSockets
Results
The team could see how the platform behaved at that scale on test infrastructure, not in production. See all case studies
Technologies Used
Technologies & Tools I Work With
Frameworks
Databases & Caching
API Design
Testing
Deployment
Observability
How I Work
Read the Code and the Metrics
Before proposing anything I read the codebase, the slow query log and the deploy history. The fix depends on what is actually wrong.
Agree on the Contract
For new work, the API contract is written and reviewed first, so client teams can start in parallel.
Test Before Changing
Tests go around the behavior that has to stay the same before any refactor starts. Then changes land in small pull requests.
Release in Stages
Each environment is validated before the next, with monitoring in place and a rollback path ready.
Hand Over
API documentation, runbooks and a walkthrough with your team, so the code stays maintainable after I leave.
How We Can Work Together
Backend Review
A short, fixed-scope review of your codebase, performance and release process. You get a written report: risks, what to fix first and a plan you can execute with or without me.
Fixed-Scope Project
A defined API, service or performance fix with a written scope, timeline and deliverables.
Monthly Retainer
Senior backend help every month: features, reviews, performance and reliability work, with predictable cost and priority response.
Not sure which fits? See how consulting engagements work or book a call.
Frequently Asked Questions
Django or FastAPI?
Django when you want the admin, the ORM and batteries included for a product backend. FastAPI when you need a lean, async service or a model-serving API. Many systems use both. If you already have one, the answer is usually to keep it.
Our backend is slow. Where do you start?
With measurements: which endpoints, under what load, and where the time goes. Most slowness comes from a small number of queries or missing caches, and fixing those first gives the biggest gain for the least change.
Can you work inside our existing codebase and team?
Yes. I follow your repo's conventions, open pull requests your team reviews and document decisions where your team will find them.
What do we get at the end?
Code merged into your repository with tests, an OpenAPI spec for new endpoints, deployment configuration, monitoring and a handover session with your team.
How long does a backend project take?
A focused performance fix or a single new service is typically a few weeks. Larger work, like splitting a monolith, is planned in phases. I give a written estimate after the first call, once I have seen the code.
Have a Backend That Is Holding You Back?
Tell me what is slow, fragile or missing, and I will tell you what I would fix first.