Interviews/Data & AI/Distributed Systems Engineer

Hire Distributed Systems Engineers
who actually build systems that survive the network

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.

Kafka · NATSetcd · ConsulRaft · PaxosFailure injectionLive 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 distributed systems engineer thinks about partitions before they think about replicas. They believe in tests under failure, not just under load. EasyEnv hands the candidate a system with a partition simulator and a consistency property to keep.

Inside a live interview

What you see when they work.

Real cluster, real partition, 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@distsys-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 Distributed Systems Engineer is hard.

CV bullets understate the difference between consensus and consistency.

Failure modes are infinite. The interview has to inject the right ones.

Tooling is opaque. The candidate has to read the source as much as the docs.

Operational empathy matters. Designs have to be debuggable.

The fit test

What we measure for a Distributed Systems Engineer.

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

Consistency reasoning

A workload and three consistency options. They explain why each fails.

Partition recovery

A simulated partition. The system returns to a sane state when it heals.

Replication design

A new feature that has to replicate. They sketch the protocol.

Failure injection

A chaos test where they predict the failure before they run it.

Tooling fluency

Kafka, NATS, etcd, Consul, raft. They use the right one.

AI collaboration

Allow AI for protocol scaffolding and grade whether they reason about edge cases the LLM skipped.

The stack we put in front of them.

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

KafkaNATSPulsarRabbitMQetcdConsulZooKeeperCassandraScyllaCockroachDBSpannerFoundationDBRaftPaxos

Sample challenges

What a Distributed Systems Engineer 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

Two leaders, one cluster

Scenario

An etcd cluster that briefly elects two leaders during a partition. Logs and disk are open.

What you learn

Whether they read the raft log before they touch the membership.

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 is good at quoting CAP and bad at predicting the workload. EasyEnv records the prompts so you see whether the candidate ran the failure injection before they kept the LLM-suggested design.

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 Distributed Systems Engineer 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 Distributed Systems Engineer, answered.

Yes. Any of these can be pre-installed with seeded data and a chaos harness.

Yes. The workspace supports network rules to inject delays, drops and reorderings.

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/Data & AI/Distributed Systems Engineer

Hire Distributed Systems Engineers
who actually build systems that survive the network

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.

Kafka · NATSetcd · ConsulRaft · PaxosFailure injectionLive 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 cluster, real partition, 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@distsys-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 Distributed Systems Engineer is hard.

CV bullets understate the difference between consensus and consistency.

Failure modes are infinite. The interview has to inject the right ones.

Tooling is opaque. The candidate has to read the source as much as the docs.

Operational empathy matters. Designs have to be debuggable.

The fit test

What we measure for a Distributed Systems Engineer.

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

Consistency reasoning

A workload and three consistency options. They explain why each fails.

Partition recovery

A simulated partition. The system returns to a sane state when it heals.

Replication design

A new feature that has to replicate. They sketch the protocol.

Failure injection

A chaos test where they predict the failure before they run it.

Tooling fluency

Kafka, NATS, etcd, Consul, raft. They use the right one.

AI collaboration

Allow AI for protocol scaffolding and grade whether they reason about edge cases the LLM skipped.

The stack we put in front of them.

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

KafkaNATSPulsarRabbitMQetcdConsulZooKeeperCassandraScyllaCockroachDBSpannerFoundationDBRaftPaxos

Sample challenges

What a Distributed Systems Engineer 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

Two leaders, one cluster

Scenario

An etcd cluster that briefly elects two leaders during a partition. Logs and disk are open.

What you learn

Whether they read the raft log before they touch the membership.

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 is good at quoting CAP and bad at predicting the workload. EasyEnv records the prompts so you see whether the candidate ran the failure injection before they kept the LLM-suggested design.

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 Distributed Systems Engineer 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 Distributed Systems Engineer, answered.

Yes. Any of these can be pre-installed with seeded data and a chaos harness.

Yes. The workspace supports network rules to inject delays, drops and reorderings.

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 Distributed Systems Engineer | EasyEnv | EasyEnv

Hire Distributed Systems Engineerswho actually build systems that survive the network

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 Distributed Systems Engineer is hard.

What we measure for a Distributed Systems Engineer.

Consistency reasoning

Partition recovery

Replication design

Failure injection

Tooling fluency

AI collaboration

The stack we put in front of them.

What a Distributed Systems Engineer interview looks like.

Two leaders, one cluster

Score the engineer, and how they work with AI.

Ready to hire a Distributed Systems Engineer who ships?

Hiring a Distributed Systems Engineer, answered.

Hire Distributed Systems Engineerswho actually build systems that survive the network

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 Distributed Systems Engineer is hard.

What we measure for a Distributed Systems Engineer.

Consistency reasoning

Partition recovery

Replication design

Failure injection

Tooling fluency

AI collaboration

The stack we put in front of them.

What a Distributed Systems Engineer interview looks like.

Two leaders, one cluster

Score the engineer, and how they work with AI.

Ready to hire a Distributed Systems Engineer who ships?

Hiring a Distributed Systems Engineer, answered.

Hire Distributed Systems Engineers
who actually build systems that survive the network

Hire Distributed Systems Engineers
who actually build systems that survive the network