Interviews/Application Development/Senior Python Developer

Hire Senior Python Developers
who actually write Python that scales past the prototype

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Django · FastAPIasyncioPostgreSQLpytest · profileLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

A senior Python developer reads the call graph as fluently as the code. They know when to reach for asyncio and when not to, when to profile and when to ship. EasyEnv hands the candidate a real Django or FastAPI codebase with a slow endpoint and a flaky test.

Inside a live interview

What you see when they work.

Real Django, real database, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@python-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Senior Python Developer is hard.

Python feels easy and rewards taste. The interview has to draw out the taste.

asyncio is misunderstood. CVs say "experienced". Workspaces show it.

ORM fluency hides query badness. The candidate has to look at SQL.

Performance work is profile-driven. Whiteboards skip the profile.

The fit test

What we measure for a Senior Python Developer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Debug a Django view

A view that returns 500 once an hour. The candidate has the traceback, the model and the queryset.

Profile a hot path

A FastAPI endpoint that exceeds its budget. py-spy and SQL logs are open.

ORM versus SQL

A queryset that produces N+1. They explain and fix without breaking the test suite.

Test taste

A flaky test that depends on time. They replace it with one that does not.

Tooling fluency

pytest, hypothesis, ruff, mypy. They reach for the right ones without ceremony.

AI collaboration

Allow Copilot or Claude and grade whether they run the test suite before they keep the patch.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

DjangoFastAPIFlaskStarletteSQLAlchemyasynciopytesthypothesisruffmypyPostgreSQLRedisCelerypy-spygunicornuvicorn

Sample challenges

What a Senior Python Developer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The list view that crawls

Scenario

A Django list view that issues 600 queries per page. The candidate has the model, the queryset and the SQL log.

What you learn

Whether they reach for select_related and prefetch_related before they cache.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes Python that compiles, often. EasyEnv records the prompts so you see whether the candidate ran the test suite and the profile before they merged what came back.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Senior Python Developer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Senior Python Developer, answered.

Yes. We can pre-load both in the workspace and switch between them per question.

Yes. pandas, polars, NumPy and SQLAlchemy are available with real seeded data.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

Interviews/Application Development/Senior Python Developer

Hire Senior Python Developers
who actually write Python that scales past the prototype

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Django · FastAPIasyncioPostgreSQLpytest · profileLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

Inside a live interview

What you see when they work.

Real Django, real database, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@python-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Senior Python Developer is hard.

Python feels easy and rewards taste. The interview has to draw out the taste.

asyncio is misunderstood. CVs say "experienced". Workspaces show it.

ORM fluency hides query badness. The candidate has to look at SQL.

Performance work is profile-driven. Whiteboards skip the profile.

The fit test

What we measure for a Senior Python Developer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Debug a Django view

A view that returns 500 once an hour. The candidate has the traceback, the model and the queryset.

Profile a hot path

A FastAPI endpoint that exceeds its budget. py-spy and SQL logs are open.

ORM versus SQL

A queryset that produces N+1. They explain and fix without breaking the test suite.

Test taste

A flaky test that depends on time. They replace it with one that does not.

Tooling fluency

pytest, hypothesis, ruff, mypy. They reach for the right ones without ceremony.

AI collaboration

Allow Copilot or Claude and grade whether they run the test suite before they keep the patch.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

DjangoFastAPIFlaskStarletteSQLAlchemyasynciopytesthypothesisruffmypyPostgreSQLRedisCelerypy-spygunicornuvicorn

Sample challenges

What a Senior Python Developer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The list view that crawls

Scenario

A Django list view that issues 600 queries per page. The candidate has the model, the queryset and the SQL log.

What you learn

Whether they reach for select_related and prefetch_related before they cache.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes Python that compiles, often. EasyEnv records the prompts so you see whether the candidate ran the test suite and the profile before they merged what came back.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Senior Python Developer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Senior Python Developer, answered.

Yes. We can pre-load both in the workspace and switch between them per question.

Yes. pandas, polars, NumPy and SQLAlchemy are available with real seeded data.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

How to Hire a Senior Python Developer | EasyEnv | EasyEnv

Hire Senior Python Developerswho actually write Python that scales past the prototype

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Senior Python Developer is hard.

What we measure for a Senior Python Developer.

Debug a Django view

Profile a hot path

ORM versus SQL

Test taste

Tooling fluency

AI collaboration

The stack we put in front of them.

What a Senior Python Developer interview looks like.

The list view that crawls

Score the engineer, and how they work with AI.

Ready to hire a Senior Python Developer who ships?

Hiring a Senior Python Developer, answered.

Hire Senior Python Developerswho actually write Python that scales past the prototype

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Senior Python Developer is hard.

What we measure for a Senior Python Developer.

Debug a Django view

Profile a hot path

ORM versus SQL

Test taste

Tooling fluency

AI collaboration

The stack we put in front of them.

What a Senior Python Developer interview looks like.

The list view that crawls

Score the engineer, and how they work with AI.

Ready to hire a Senior Python Developer who ships?

Hiring a Senior Python Developer, answered.

Hire Senior Python Developers
who actually write Python that scales past the prototype

Hire Senior Python Developers
who actually write Python that scales past the prototype