Interviews/Specialty Stacks/FastAPI Developer

Hire FastAPI Developers
who actually ship async Python that types itself

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.

FastAPIPydantic 2asyncio · httpxuvicorn · gunicornLive 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 great FastAPI developer treats Pydantic as a domain language and async as the default. The good ones avoid sync-DB-in-async traps, design dependency injection that does not leak, and ship OpenAPI that other teams can use. EasyEnv hands the candidate a real FastAPI service with a sync call hidden inside an async path.

Inside a live interview

What you see when they work.

Real FastAPI service, real async, 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@fastapi-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 FastAPI Developer is hard.

FastAPI looks simple and rewards async fluency. The interview has to find that.

Pydantic 1 versus 2 fluency is uneven.

Sync-DB-in-async is the most common production bug. Few candidates can spot it.

Dependency overrides in tests confuse many candidates.

The fit test

What we measure for a FastAPI Developer.

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

Async correctness

A sync DB call inside an async endpoint. They explain and fix.

Pydantic 2 fluency

A schema with validation drift. They migrate without breaking callers.

Dependency injection

A Depends that leaks DB sessions. They scope correctly.

Streaming and websockets

A streaming endpoint that buffers. They wire backpressure.

OpenAPI as contract

A schema that drifts from reality. They align tags and responses.

AI collaboration

Allow AI for schema writing and grade whether they ran the schema-validation tests after.

The stack we put in front of them.

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

FastAPIPydantic 2SQLAlchemy 2asyncpghttpxuvicorngunicornpytest-asynciostarletteOpenAPIAlembicRedisarqSentryOpenTelemetry

Sample challenges

What a FastAPI 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 sync call in async

Scenario

An async endpoint calling SQLAlchemy sync session. p99 latency tanks under load.

What you learn

Whether they reach for async session, not a thread executor as a band-aid.

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 async FastAPI that blocks on a sync call buried in a Depends. EasyEnv records prompts so you see whether the candidate re-ran the load test after the LLM-suggested change.

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 FastAPI 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 FastAPI Developer, answered.

Yes. OIDC, JWT and API key flows can all be pre-wired.

Yes. Either Pydantic 1 or 2 can be pinned with a migration target.

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/Specialty Stacks/FastAPI Developer

Hire FastAPI Developers
who actually ship async Python that types itself

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.

FastAPIPydantic 2asyncio · httpxuvicorn · gunicornLive 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 FastAPI service, real async, 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@fastapi-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 FastAPI Developer is hard.

FastAPI looks simple and rewards async fluency. The interview has to find that.

Pydantic 1 versus 2 fluency is uneven.

Sync-DB-in-async is the most common production bug. Few candidates can spot it.

Dependency overrides in tests confuse many candidates.

The fit test

What we measure for a FastAPI Developer.

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

Async correctness

A sync DB call inside an async endpoint. They explain and fix.

Pydantic 2 fluency

A schema with validation drift. They migrate without breaking callers.

Dependency injection

A Depends that leaks DB sessions. They scope correctly.

Streaming and websockets

A streaming endpoint that buffers. They wire backpressure.

OpenAPI as contract

A schema that drifts from reality. They align tags and responses.

AI collaboration

Allow AI for schema writing and grade whether they ran the schema-validation tests after.

The stack we put in front of them.

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

FastAPIPydantic 2SQLAlchemy 2asyncpghttpxuvicorngunicornpytest-asynciostarletteOpenAPIAlembicRedisarqSentryOpenTelemetry

Sample challenges

What a FastAPI 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 sync call in async

Scenario

An async endpoint calling SQLAlchemy sync session. p99 latency tanks under load.

What you learn

Whether they reach for async session, not a thread executor as a band-aid.

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 async FastAPI that blocks on a sync call buried in a Depends. EasyEnv records prompts so you see whether the candidate re-ran the load test after the LLM-suggested change.

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 FastAPI 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 FastAPI Developer, answered.

Yes. OIDC, JWT and API key flows can all be pre-wired.

Yes. Either Pydantic 1 or 2 can be pinned with a migration target.

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 FastAPI Developer | Async + Pydantic | EasyEnv | EasyEnv

Hire FastAPI Developerswho actually ship async Python that types itself

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 FastAPI Developer is hard.

What we measure for a FastAPI Developer.

Async correctness

Pydantic 2 fluency

Dependency injection

Streaming and websockets

OpenAPI as contract

AI collaboration

The stack we put in front of them.

What a FastAPI Developer interview looks like.

The sync call in async

Score the engineer, and how they work with AI.

Ready to hire a FastAPI Developer who ships?

Hiring a FastAPI Developer, answered.

Hire FastAPI Developerswho actually ship async Python that types itself

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 FastAPI Developer is hard.

What we measure for a FastAPI Developer.

Async correctness

Pydantic 2 fluency

Dependency injection

Streaming and websockets

OpenAPI as contract

AI collaboration

The stack we put in front of them.

What a FastAPI Developer interview looks like.

The sync call in async

Score the engineer, and how they work with AI.

Ready to hire a FastAPI Developer who ships?

Hiring a FastAPI Developer, answered.

Hire FastAPI Developers
who actually ship async Python that types itself

Hire FastAPI Developers
who actually ship async Python that types itself