Python specialists
Accra, Ghana
Python isn't one job.
It's four.
A Python web engineer is not a Python data engineer. A data engineer is not an ML engineer. We place all four — as specialists, not generalists.
Pick a track to explore
5–10 business days
Median time from request to shortlist
2-week paid trial
See them work before committing
Free replacement
Within 30 days if it's not a fit
5 timezone overlaps
GMT, WAT, EAT, CET, EST
Web & API track
Django, FastAPI, Flask
Backend engineers who build REST APIs, admin panels, and authentication services. Django for full-stack, FastAPI for async-first APIs.
Rate range
Mid
18K – 28K
Senior
28K – 45K
Lead
45K – 65K
GHS per engineer / month. USD equivalent: $1,600 – $5,800.
What they deliver
- Versioned REST APIs with OpenAPI docs
- Django admin panels for internal teams
- Auth flows — JWT, OAuth2, SSO
- Celery-backed queues and scheduled jobs
- Third-party integrations (payments, SMS, identity)
- Full test coverage with pytest + factory_boy
Typical projects
- SaaS backends for React/Vue front-ends
- Customer self-service portals
- Internal admin and ops tools
- Public APIs for mobile apps
The craft
Real web code from real projects.
Not tutorials. Production patterns we ship — with error handling, idempotency, and the details that separate hobby code from systems that run businesses.
web & api.pyEcosystem
The tools for this track.
Not a generic Python list. These are the specific tools our web & api engineers use in production.
Django
Full-stack framework. Admin panels, ORM, auth — batteries included.
FastAPI
Async-first API framework with automatic OpenAPI docs and Pydantic validation.
PostgreSQL
Default database for transactional and analytical workloads.
Redis
Caching, sessions, and Celery broker for background jobs.
Celery
Distributed task queue. Retries, scheduling, and monitoring.
Docker
Containerised deployments for every Python service we ship.
Also fluent in
Popular architectures
Six stacks we build with most often.
Every project is different, but these are the recurring patterns we reach for — and why we reach for them.
FastAPI + React
The default modern stack for building product APIs that power a React or mobile front-end. Async, typed, fast.
Stack
Used for
SaaS backends, mobile app APIs, customer portals
Django + HTMX
Full-stack Django with HTMX for interactivity — no separate front-end, faster to ship, easier to maintain.
Stack
Used for
Internal tools, CRMs, ops panels, government systems
Airflow + dbt + Postgres
Classic ELT: Airflow orchestrates, dbt transforms, Postgres serves. Testable and observable end to end.
Stack
Used for
Analytics warehouses, BI, compliance reporting
PyTorch + FastAPI + MLflow
Train with PyTorch, serve with FastAPI, track experiments with MLflow. Monitoring and drift detection built in.
Stack
Used for
Fraud detection, recommendations, document AI
Celery + Redis + Workers
Reliable distributed task processing with retries, scheduling, and monitoring. Every job is idempotent.
Stack
Used for
Notifications, batch processing, media handling
Scrapy + Playwright + S3
Scheduled scraping with headless browsers and structured extraction. Idempotent writes back to storage.
Stack
Used for
Price monitoring, market intelligence, data gathering
Honest boundaries
When Python is the right choice — and when it isn't.
We'd rather tell you upfront than sell you the wrong stack. Here's the honest picture.
When Python wins
Web backends
Django and FastAPI scale to serious production traffic when written well.
Data pipelines
Airflow, pandas, and dbt are the industry standard for a reason.
ML and AI
The whole ML ecosystem lives in Python. Nothing else comes close.
Automation & scripts
The fastest path from idea to working script.
Data analysis
Jupyter, pandas, and matplotlib for exploration and reporting.
Integration glue
Bridging systems that don't know about each other.
When it doesn't
High-throughput realtime
Node.js and Go handle millions of concurrent connections better.
Low-latency trading
C++, Rust, or Java for microsecond-level latency requirements.
Mobile native
Kotlin, Swift, or React Native — Python isn't a mobile platform.
Front-end heavy UI
React, Vue, and Angular own this space. Python is server-side.
Compare
Python vs Node.js vs Go.
Three popular backend languages, honestly compared. We work in all three — here's when we recommend Python.
| Factor | Python | Node.js | Go |
|---|---|---|---|
| Learning curve | Easiest — readable, minimal syntax | Easy but async/await and event loop need learning | Simple syntax, more verbose type system |
| Raw throughput | Moderate — fine for most apps, not for max throughput | Very high for I/O-bound workloads | Very high for both I/O and CPU |
| Data & ML ecosystem | Unmatched — pandas, PyTorch, scikit-learn, everything | Weak — TensorFlow.js exists but limited | Minimal — no serious ML libraries |
| Best-fit projects | APIs, data, ML, automation, scripts | Realtime APIs, WebSockets, gateways, BFFs | High-throughput services, CLIs, infra tooling |
| Async model | async/await with asyncio — solid but GIL limits | Native event loop — great for concurrency | Goroutines — simplest concurrency model |
| Hiring pool | Very large — especially for data/ML roles | Large — JS devs everywhere | Smaller — more expensive to hire |
Engagement models
Three ways to work with us.
Same standard across every model — vetted engineers, signed NDA, full IP transfer, free replacement guarantee.
Full-time
40 hrs / week
Best for
Long-term feature work
- Dedicated engineer, your time zone overlap
- Monthly rolling contract, cancel any time
- Best rate per hour
- Includes project manager
Part-time
20 hrs / week
Best for
Ongoing maintenance
- Same vetted engineers, half-time
- Weekly billing, no long commitment
- Great for steady-state teams
Project-based
Fixed scope
Best for
MVPs and one-off builds
- Defined deliverable, defined price
- Milestone-based billing
- Fixed timeline with guarantees
Pricing by track
Rates differ by track. Here's why.
An ML engineer costs more than an automation engineer — different talent pools, different market rates. We list them honestly.
Terms: Rates are indicative, exclusive of taxes. USD at GHS 11.00/USD (April 2026). Volume discounts on 3+ engineers. Contracts over 6 months get preferred rates — ask. GHS invoiced for Ghana clients, USD for international. Enterprise and government tenders: custom pricing on request.
Vetting process
Four filters before
you see a candidate.
We reject most engineers who apply. Only those who pass all four stages make it to your shortlist.
Technical screen
Live coding covering Python fundamentals, framework depth, and system design.
Code review
We read their real code — public repos or a paid trial task. No multiple-choice quizzes.
Communication check
Written and verbal. We don't place engineers who can't explain decisions clearly.
Reference check
We speak to at least one former manager or senior colleague. Always.
Zero risk
Six guarantees. In writing.
No exceptions.
Trial period, no commitment
Work with your engineer first. If it's not right within two weeks, we replace them — free.
NDA before we talk details
Signed before any project information changes hands. Your ideas stay yours from the first call.
You own every line of code
No licensing. No reuse clauses. No fine print. Everything we write for you belongs to you.
Cancel with 30 days' notice
No termination fees, no lock-in, no arguments. Stop the engagement whenever you need to.
Free replacement, no questions
If the fit isn't right, we swap the engineer at no cost. Same vetting bar, same standard.
Vetted bench
Every engineer passes technical, communication, code, and reference checks before you see them.
Process
From request to engineer
in four steps.
Tell us the role
Share the track, seniority, and start date. We confirm we can fill it — usually within hours.
We send candidates
Within 5–10 business days, you receive 2–3 pre-vetted Python engineers with portfolios and code samples.
You interview
You run your own interviews. We don't push candidates you don't love.
Trial or hire
2-week paid trial. Convert to full engagement if it works. We replace — free — if not.
Sectors we serve
Industries we build for.
Every sector runs its own systems. Here's what we build in each — with this framework.
Media & Entertainment
Streaming, publishing, and creative platforms
What we build
- Recommendation engines
- Content tagging ML
- Trend analysis
Manufacturing
Production planning, quality control, and MES
What we build
- Predictive maintenance
- Quality ML
- Process optimisation
Healthcare
Patient records, appointments, and clinical workflows
What we build
- Clinical data pipelines
- Diagnostic ML
- Claims processing
Banking and Finance
Core banking, payments, and lending
What we build
- Risk engines
- Fraud detection
- Algorithmic backtesting
Education and E-Learning
Admissions, student portals, and e-learning
What we build
- Learning analytics
- Assessment engines
- Recommendation systems
Travel and Tourism
Bookings, guest journeys, and travel ops
What we build
- Dynamic pricing engines
- Demand forecasting
- Route optimisation
Retail and Ecommerce
Storefronts, checkout, and marketplaces
What we build
- Demand forecasting
- Recommendation engines
- Price optimisation
Real Estate
Listings, tenant portals, and property ops
What we build
- Valuation models
- Lead scoring
- Market forecasting
Agricultural Technology
Farm platforms, agri marketplaces, and supply chains
What we build
- Yield prediction models
- Satellite image analysis
- Pest detection
Logistics & Transport
Fleet, routes, and freight platforms
What we build
- Route optimisation
- ETA prediction
- Fleet telemetry analysis
GovTech and Public Sector
Citizen services, registries, and public platforms
What we build
- Policy modelling
- Fraud detection in benefits
- Statistical reporting
Legal and Land Services
Case management, land verification, and compliance
What we build
- Case management, land verification, and compliance
FAQ
Common
questions.
Everything people usually want to know before hiring Python engineers through us.
Still have questions?Contact
Which Python
do you need?
Tell us the track, seniority, and timeline. We'll send pre-vetted candidates within 5–10 business days.
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