Hire Python Developers

Hire Python developers for the three jobs Python is most often hired for: web back ends in Django or FastAPI, data pipelines and reporting, and the automation and AI integration work that sits between systems. PS3G’s Python engineers have done all three in production and know which patterns belong to which job. They join your team as named individuals or as a dedicated team, for organizations of every size: a founder building a first API and admin, an operations team whose scripts have quietly become critical infrastructure, or a data group inside a larger organization that needs pipelines it can trust.

Hire Python developers who are managed, not just placed

The Python engineers you hire through PS3G come from our own backend, data and AI development practices, where Python is the working language. They are PS3G employees, screened by our senior engineers and supported by a technical lead and an account manager for the whole engagement. We are an engineering firm rather than a staffing agency, which matters most with Python: the language is easy, the systems built in it are not, and an engineer who can ask a senior colleague about a pipeline design or a model-serving problem is worth more than one working alone.

Python rarely owns a whole system. Our engineers are used to Python services sitting next to .NET or Node.js applications, a React front end calling a FastAPI back end, and pipelines feeding SQL Server or PostgreSQL databases that Power BI reads.

What they can do for you

Python developers for hire through PS3G are matched to one of these patterns, because the skills differ more than the language suggests.

• Web back ends and APIs. Django for applications that need an admin, authentication and an ORM out of the box; FastAPI for typed, fast APIs that serve a front end, a mobile app or other services.
• Data pipelines. Ingesting files, APIs and databases into a warehouse with pandas, SQLAlchemy, Airflow or cloud-native schedulers, with validation, logging and reruns designed in. See data engineering.
• Automation that outgrew scripts. Turning the collection of scripts that run your reports, reconciliations and file transfers into tested, scheduled, monitored jobs.
• AI integrations. Calling language-model APIs, building retrieval pipelines, and wrapping models in services, with the logging and evaluation needed to run them.
• Reporting and analysis tooling. Internal dashboards and notebooks turned into shareable, repeatable outputs.
• Legacy Python upgrades. Python 2 to 3 migrations, dependency cleanup, type hints, and tests for code nobody wants to touch.

Seniority levels

A mid-level Python developer builds endpoints, pipeline steps and jobs to a defined design, writes tests and follows the project’s packaging and style conventions. A senior developer chooses between Django and FastAPI for a given service, designs the data model and the pipeline’s failure handling, sets up packaging, environments and CI, and reviews the mid-level work. A lead engineer owns a platform of services and pipelines, decides what runs where, and works with your analysts, product owners or data scientists on priorities. For pipelines and AI work, start with a senior engineer; the costly mistakes are in the design.

How hiring works

1. Brief. A first conversation on which of the three jobs you are hiring for, the framework and Python version, the databases and cloud, how code is packaged and deployed today, and the reporting line and hours you need.
2. Vetted profiles in days. A short list of Python engineers matched to that job, with the systems they have built and their availability.
3. Interviews. Your team interviews each candidate. For back-end roles we suggest a live session on an endpoint; for data roles, a session on a failing pipeline step and how to make it rerunnable.
4. Start. Access to repositories, environments and data, a walkthrough of how things run today, and first tickets that touch deployment and data early.
5. Scale monthly. Add a data engineer when the pipeline list grows, drop to part-time once jobs are stable, or convert an individual into a dedicated team, with notice.

Tell us which Python job you are hiring for and we will send matching profiles.

Vetting: a technical screen by our own engineers

Senior PS3G engineers screen every Python developer against the job they will do. For back-end roles, the candidate reads a Django or FastAPI service with planted problems (an N+1 query in a serializer, a blocking call inside an async route, a missing database index, a migration that would lock a large table, user input passed to a shell) and explains each. For data roles, they are given a pipeline that fails halfway and asked how to make it idempotent, how to validate inputs, how to handle schema changes and how they would know it broke. Everyone is asked about virtual environments, dependency pinning, type hints, testing with pytest and how they would deploy what they wrote.

The pitfalls when you hire Python developers come from the language’s reach. Python is taught everywhere, so many candidates can write scripts but have never structured a package, written tests or deployed a service. Data scientists are often hired as data engineers and struggle with reliability and scheduling. Back-end candidates sometimes know a framework’s tutorial and not its ORM’s cost. And async Python is misunderstood more often than it is used correctly. Our screen is built around these gaps.

Individual developers vs a dedicated team vs a fixed-scope project

You can hire backend developers or data engineers individually into your team, engage a dedicated team led by PS3G, or hand us a defined system to build as a project.

Option	Who manages	Fits when	Example
Individual Python developers	Your technical or data lead	You have the systems and a process, and need more hands or a specific skill such as FastAPI or Airflow	A senior Python engineer joining an analytics team to rebuild its nightly pipelines
Dedicated Python team	A PS3G lead, against your priorities	You own the roadmap but want the back end or the data platform run as a stream of work	Two developers, a data engineer and a lead maintaining a Django product and its reporting warehouse
Fixed-scope project	PS3G owns delivery	The scope is defined and you want an outcome at a fixed price	A FastAPI service and retrieval pipeline that answers questions over your documents, delivered with evaluation and monitoring

Individuals and dedicated teams run monthly under our staff augmentation terms and scale with notice. Projects are quoted as a whole. Keeping the jobs and services running afterwards under a defined SLA is a managed service, and a data or AI readiness assessment, before you commit to building, is advisory. We begin with a first conversation, a short assessment and a written proposal that lists roles, seniority, location and monthly cost. Hourly rates are not something we publish.

Related services

• Hire developers and dedicated teams: every technology we staff.
• AI development: where our Python engineers do their model and retrieval work.
• Python development services: fixed-scope Django, FastAPI and pipeline builds.
• Data engineering: pipelines, warehouses and the reporting layer.
• IT staff augmentation: monthly terms, replacements and IP ownership.
• IT staffing: analysts, QA and other roles alongside your developers.

Frequently asked questions

Should I hire Django developers or FastAPI developers?

Django when you need an application with an admin, users, permissions and an ORM quickly, and when the team values convention. FastAPI when the service is mainly an API for a front end, a mobile app or other services, and typed request and response models matter. Many systems use both. Tell us what the service does and we will send engineers who have shipped the right one.

Can I hire data engineers through this page, or only web developers?

Both. Data engineering is one of the three jobs we match Python engineers to, and the profiles for a data role will show pipeline tools, warehouses and scheduling experience rather than web frameworks. For warehouse design and BI, we can add a specialist from our data practice.

Do your Python developers work on AI and machine learning?

Yes, for integration and application work: calling model APIs, building retrieval pipelines, evaluating outputs and serving models. For roles centered on model training, experimentation or MLOps, see our page on hiring AI developers and machine learning engineers, where the screen is different.

Can a Python developer take over scripts written by a non-developer?

This is one of the most common requests. A senior engineer will inventory the scripts, add tests around the ones that matter, move credentials out of the code, put them on a scheduler with logging and alerts, and then refactor in order of risk. The scripts keep running while that happens.

Where are your Python developers located?

In the United States and at our India delivery center. Pipeline and automation roles often suit a shifted schedule, because overnight jobs can be checked before the US day begins; back-end roles are scheduled for live overlap with your team. Account management is in Wilmington, Delaware, and the proposal prices each role by location.