Staff augmentation
Senior engineers who join your stand-ups and work in your tools.
Best when
You have a roadmap and need more capacity or a specific skill.
Hire senior Python developers
Python developers who write production software, not only notebooks: typed FastAPI services, data pipelines that can be re-run safely, and models that are deployed, versioned and monitored.
Short answer
elitics provides senior Python developers from Prishtina who build FastAPI services, data pipelines and machine learning features with Pandas, NumPy and TensorFlow, typed and tested, packaged in Docker and deployed through CI. You interview the developers, they start about 48 hours after you approve their profiles, and team extension costs €45–65 an hour with a two-week trial.
- per engineer-hour, month to month
- €45–65
- from profile approval to start
- ~48 h
- typed services with validated input and output
- FastAPI
- NumPy and TensorFlow for data and models
- Pandas
What our Python developers build
- Back-end services
- FastAPI services with typed request and response models, authentication, background tasks and generated API documentation.
- Data pipelines
- Ingestion from APIs, files and databases into your warehouse or Postgres, scheduled, logged and safe to re-run after a failure.
- Machine learning in production
- Forecasting, classification and scoring models trained with TensorFlow and the Python data stack, served behind an API and monitored for drift.
- Automation and internal tools
- Scripts that grew into critical systems, turned into tested, packaged services with proper configuration and logs.
What a senior Python developer should own
Python is easy to write and easy to write badly. These habits separate production code from prototypes.
- Types and validation
- Type hints checked in CI and data validated at every boundary, so bad input fails early with a clear error.
- Reproducible environments
- Pinned dependencies, a lock file and Docker images, so the code runs the same on a laptop, in CI and in production.
- Re-runnable pipelines
- Idempotent steps, partitioned loads and backfills that do not create duplicates when a job runs twice.
- Models as software
- Versioned training data and models, evaluation before deployment, and monitoring of input drift and prediction quality.
Questions to ask a Python developer
These questions show whether a candidate has shipped Python to production or only used it for analysis.
- 01
A nightly import failed halfway. What happens when you re-run it?
Nothing is duplicated: loads are idempotent, by partition or upsert key, and the job resumes or restarts cleanly.
- 02
How do you keep dependencies from breaking production?
A lock file, pinned versions, automated update PRs with tests, and the same Docker image from CI to production.
- 03
When is async worth it in FastAPI?
For I/O-bound work such as calls to other services or databases with async drivers; CPU-heavy work belongs in a worker process instead.
- 04
How do you know a deployed model is still good?
Track input distributions and prediction quality against labelled samples, and alert when they move beyond agreed thresholds.
- 05
A Pandas job runs out of memory. What are your options?
Read in chunks, choose smaller dtypes, push filtering down to the database, or move the step to a tool built for larger data.
How hiring an engineer works
- 01
Tell us the role
Stack, seniority, start date and the hours you need to share. A call with our engineering lead takes 30 minutes.
- 02
Review profiles
You receive engineer profiles matched to your stack and interview the ones you choose.
- 03
Start in about 48 hours
NDA and IP assignment are signed, and the engineers are set up in your repositories and tools.
- 04
Two-week trial
If you are not satisfied, you do not pay for those two weeks. An engineer who is not the right fit is replaced at no extra cost.
Typical set-ups
- One Python developer
- Joins your data or back-end team to add capacity on services or pipelines.
- Data pair
- A Python developer and a data engineer who own ingestion, models and the API that serves them.
- AI squad
- Python and AI engineers with a full-stack developer to put a model or AI feature into your product.
Ways to work with us
Dedicated squad
A cross-functional team (product, engineering, QA, DevOps) that owns a product or feature.
Best when
You want a product built or rebuilt without growing headcount.
Build-Operate-Transfer
Your own development center in Kosovo, set up and run by us.
Best when
You plan a long-term engineering presence in Europe.
Prefer a delivered project? Data Engineering Services
Common questions
Do your Python developers also do AI work?
Yes. Many of our AI features are built in Python. For language-model products, see our AI engineers; for classical machine learning and data, Python developers are the usual fit.
Which Python frameworks do you use?
FastAPI for services, Pandas and NumPy for data work and TensorFlow for machine learning. We work in your existing frameworks when you already have them.
Can they work with our data warehouse?
Yes. They connect to your warehouse or Postgres through your access controls; personal data stays in your environment.
Is there a trial period?
Yes. New engagements start with a two-week trial. If you are not satisfied, you do not pay for those two weeks.
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Let’s build what comes next.
Tell us what you need to build or scale. You will get a proposal and estimate within 24 hours.