United Kingdom · Technical roles · Mid-Level (2-5 years)

Chaos Engineer

Here is the whole job, in plain words. What it is, a real day, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

Experience bandMid-Level (2-5 years)
Direct reportsNo direct reports
Reports toSenior Chaos Engineer
UK framework levelUsually a coordinator, or early in a professional job

Also advertised as Resilience Engineer · Site Reliability Engineer (SRE) - Chaos Focus · Production Reliability Engineer

Built on an analysis of 43,079 real UK job descriptions · grounded in qualifications employers recognise

Start with a free Future Fluency check, tuned to Chaos Engineer

Ten quick questions, one per Future Fluency, asked against this role rather than a generic one. About five minutes, and no card.

Start the check, free

1What this role really is

You'll be the person who deliberately breaks things (safely, mind you!) to make sure they don't actually break when it really matters. Think of it as stress-testing our systems to find weaknesses before our customers do. We're talking about making our software and infrastructure more robust, more reliable, and ultimately, more trustworthy. It's a bit like being a detective, but instead of solving crimes, you're preventing them by exposing vulnerabilities in a controlled environment. You'll work closely with development and operations teams, helping them understand where their systems might fail and how to build them stronger. Honestly, it's a pretty crucial role in keeping everything running smoothly, especially as our systems get more complex.

2What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Gremlin / Chaos MeshIntermediate

Executing pre-defined attack scenarios (e.g., CPU, Blackhole) with a detailed runbook. You'll be able to halt experiments safely and confidently.

Datadog / PrometheusIntermediate

Building complex dashboards and SLO-based alerts from scratch. You'll use advanced query languages (Datadog query lang, PromQL) to isolate the impact of your experiments and identify anomalies.

GrafanaIntermediate

Creating and maintaining sophisticated dashboards with dynamic variables and annotations to correlate experiment events with system behaviour. This is how you'll visualise your findings.

TerraformIntermediate

Writing and maintaining Terraform modules to provision ephemeral test environments for your experiments. You'll also understand how to identify the infrastructure targeted by an experiment.

Kubernetes (kubectl)Intermediate

Expertly debugging applications within Kubernetes. You'll understand controllers, operators, and network policies to design targeted experiments within our containerised environments.

Python (requests, boto3)Intermediate

Developing robust automation frameworks to orchestrate GameDays, automatically gather evidence, and generate reports. You'll be writing scripts to make your life easier and our experiments more efficient.

3What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choice	Coming in	Where you are now	The step above
Experiment Design & Scope	Proposes designs for review; scope is tightly defined by supervisor.	Independently designs experiments for specific services; consults on blast radius for critical systems; seeks approval for production experiments.	Designs complex, multi-service experiments; defines blast radius and safety protocols for high-impact scenarios; approves production experiments.
Tooling & Automation Choices	Uses existing tools and follows prescribed scripts.	Proposes minor improvements to existing scripts or tooling; selects appropriate fault injection techniques from approved list.	Evaluates new chaos engineering tools; designs and implements significant automation frameworks; makes recommendations for platform evolution.
Incident Response during Experiment	Immediately escalates any unexpected behaviour or signs of impact beyond blast radius.	Executes pre-defined rollback procedures; escalates if rollback fails or impact is severe/uncontained.	Leads incident response during complex experiments; makes real-time decisions on experiment continuation or abortion; coordinates multiple teams.
Stakeholder Communication	Communicates status to immediate team and supervisor.	Communicates experiment plans and results to development teams and SREs; handles routine questions and objections.	Presents findings to senior engineering leadership; influences architectural decisions based on resilience insights; manages challenging stakeholder conversations.

4How you'll be judged

The scoreboard, honestly: the hard targets, how often each one is actually looked at, and the quiet human signals that never make it onto a dashboard.

GameDays Executed

The number of chaos engineering GameDays you successfully plan and run each quarter.

Target · > 5 GameDays per quarter

You run six GameDays in Q1, covering three different critical services, each identifying at least one new resilience improvement.

Post-Experiment Report Timeliness

How quickly you get the findings and action items from a GameDay documented and shared.

Target · 100% of reports filed within 24 hours of experiment completion

After a GameDay on Tuesday afternoon, the initial report draft is in the shared document by Wednesday morning, ready for review.

Runbook Adherence & Safety

The percentage of experiments executed strictly following the agreed-upon runbook, with no unintended 'blast radius' or production impact.

Target · > 98% adherence to runbook, 0 production incidents caused by experiments

You run ten experiments, and in one, a minor deviation from the runbook occurred, but it was quickly corrected with no impact. No production incidents were caused by any of your experiments.

Identified Vulnerabilities

The number of unique, critical failure modes or resilience gaps you identify through your experiments.

Target · > 1 critical vulnerability identified and documented per GameDay, on average

In a GameDay targeting our payment processing service, you discover that a specific network latency scenario causes a deadlock, which was previously unknown.

Proactive Problem Identification

Your ability to spot potential weaknesses in systems before they're even assigned to you, or before they become incidents.

You'll be suggesting new experiment ideas based on recent incidents (internal or external), architectural reviews, or new service deployments. Your ideas will often pre-empt issues that others haven't considered yet. People will come to you asking 'what should we break next?'

Clear Communication During GameDays

How well you communicate the status, findings, and any potential risks during live experiments.

During a GameDay, you'll keep all participants updated, clearly explaining what's happening and what to look for. No one will be left guessing. Post-experiment, your debriefs will be concise, actionable, and easy for development teams to understand and act upon. You'll get feedback like 'that was really clear' or 'I knew exactly what was going on'.

Learning & Adaptation

Your willingness to learn from both successful and unsuccessful experiments, and to adapt your approach based on new information.

You'll actively participate in post-mortems, not just for your own experiments but for wider incidents. You'll adjust your experiment designs based on feedback or unexpected outcomes. You'll be seen as someone who's always trying to improve the process, not just follow it blindly. You'll share 'lessons learned' with the team.

Collaboration & Influence

How effectively you work with other engineering teams to get their buy-in and support for chaos experiments.

Development teams will generally be willing to participate in your GameDays, seeing the value rather than just the disruption. You'll be able to explain the 'why' behind experiments in a way that resonates with them. You'll get requests from teams asking you to test their new services, which is a big win.

5Would you like it

The honest version. What people enjoy, and what grinds them down.

What people enjoy

Solving Complex Puzzles

You'll spend a lot of time digging into intricate system architectures, trying to figure out how different components interact and where the hidden failure points might be. It's like being a detective for system weaknesses, which is incredibly satisfying when you find something critical.

Spending an afternoon mapping out a new service's dependencies, then designing an experiment that targets a specific, non-obvious network path to see if it breaks.

Making a Tangible Impact on Reliability

Your work directly prevents outages. You'll see the results of your experiments leading to actual code changes or architectural improvements that make our systems more robust. It's very rewarding to know you're making a real difference to customer experience.

After a GameDay, a development team implements a circuit breaker you recommended, and you later see it prevent a cascading failure during a real-world incident.

Continuous Learning & Technical Deep Dive

You'll constantly be learning about new technologies, distributed system patterns, and failure modes. This role demands a deep understanding of how systems work at a fundamental level, which is perfect if you love to get into the nitty-gritty details and expand your technical knowledge.

Researching a new type of database failure seen in an industry post-mortem, then figuring out how to simulate it in our own environment to test our resilience.

What frustrates people

The Culture of Fear: You'll constantly battle the perception that you're just there to 'break things' and make other teams look bad, rather than being a partner in improving reliability. It takes a lot of diplomacy to get past this.
The 'Not In My Backyard' Syndrome: Engineering teams often agree chaos engineering is a brilliant idea... for everyone else's service. Getting them to volunteer their own service for an experiment can be a major political battle, requiring patience and persuasion.
Observability Gaps: You'll plan a perfect experiment, only to realise the target service has no meaningful metrics or logs, making it impossible to actually know if your experiment had any effect at all. This means you can't prove your hypothesis or identify the root cause.
The Blame Game: When a *real* production incident occurs, you might be one of the first people blamed, with everyone asking, 'Was this one of your experiments?!' even when it's 3 AM on a Saturday and completely unrelated. It's unfair, but it happens.
The 'Success Theatre' Paradox: Sometimes, an experiment runs perfectly, and nothing breaks. While this proves resilience, stakeholders might occasionally view it as a 'waste of time,' failing to appreciate that proving a system is robust is, in itself, a successful outcome.
Documentation Overhead: You'll spend a fair chunk of your time writing proposals, risk assessments, and getting approvals, sometimes feeling like only 20% of your time is actually spent running experiments and engineering solutions. Yes, it's necessary, but it can be a grind.

What this role does not give you

A quiet, predictable routine: Expect frequent shifts in focus based on new incidents, service deployments, or emerging risks. If you thrive on strict routine, this probably isn't for you.
Instant gratification on every project: Not all experiments will yield dramatic findings, and some improvements will take months to implement. You'll need patience.
Working in isolation: This role is highly collaborative. If you prefer to just put your head down and code without much interaction, you'll struggle to get buy-in and make an impact.

6Who you work with

This role directly improves the availability and reliability of our core services. By proactively identifying and helping to fix vulnerabilities, you'll reduce the frequency and impact of production incidents, which means happier customers and a more stable platform. It also helps embed a culture of resilience thinking across our engineering teams, making everyone build better software from the start. Honestly, it's about building trust, both internally and with our users.

Inside the business

Development Teams (the ones who build the services)
Site Reliability Engineers (SREs)
Product Managers (who care about uptime)
Operations Teams (who keep the lights on)
Security Teams (who also look for weaknesses)

Outside the business

N/A (this role is primarily internal-facing)

7What you need before you start

Not a wish list. The things you would be expected to already have.

At least 2-3 years of hands-on experience in a DevOps, SRE, or Software Engineering role, with a strong focus on system reliability or infrastructure.
Demonstrable experience with at least one major cloud provider (AWS, Azure, GCP) and container orchestration (Kubernetes).
A solid understanding of networking fundamentals (TCP/IP, DNS, load balancing) and how network failures impact applications.
Proven ability to write clear, concise technical documentation and reports.
Experience debugging complex distributed systems and reading through logs and metrics to identify issues.

8What to practise next

Where the job is going, and what to do about it starting this week.

Proactive Failure Prediction with Machine Learning

Instead of just reacting to failures or simulating known ones, the next step is to predict them. As our systems generate more data, using ML to spot anomalous patterns that indicate impending failure will become critical. This moves us from reactive to truly proactive resilience.

Time-series anomaly detection · Predictive modelling for system health · Feature engineering for reliability data · Integration with chaos tooling

This quarter: Take an online course on time-series analysis or anomaly detection (e.g., on Coursera or Udemy).
Next quarter: Start exploring open-source ML libraries (like scikit-learn or TensorFlow) for basic predictive modelling on historical incident data.
Month 6: Propose a small pilot project to apply anomaly detection to one critical service's metrics.
Month 9: Work with a data scientist (if available) to build a simple predictive model for a specific failure type.

Quick win: Start by simply visualising correlations between different metrics and incident occurrences in Grafana. It's a low-effort way to start thinking predictively.

9Staying current once you are in

What people here do to keep up

Regularly contributing to open-source projects, especially those related to chaos engineering, SRE, or cloud-native tooling.
Attending industry conferences (e.g., KubeCon, SRECon, Chaos Conf) to stay current with trends and network with peers.
Participating in online communities and forums (e.g., Slack channels, Reddit) focused on reliability engineering and distributed systems.
Taking advanced online courses on specific technical topics like advanced Kubernetes, distributed tracing, or specific programming languages.
Presenting your work or sharing lessons learned at internal 'lunch and learn' sessions or external meetups.

10How the AI economy is changing work like this

Before we ask anything of you, here's what we can already say about AI and work of this kind:

The new skill this role is being asked for: Prompt Engineering & LLM Integration

Honestly, AI is already transforming how we analyse data, draft reports, and even write code. Competitors are using tools like GPT to draft experiment reports in minutes that used to take hours. Engineers who figure this out will seriously outproduce their peers.

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

Your PlanIllustration

Built for Chaos Engineer

5 units that map to this job, from the qualifications that cover it.

Supervise the set up and operation of special effects for live performancesPearson EDI · covers 1 of 1 standardsLevel 3
Work safely in an explosives environmentInstitute of Commercial Management · covers 1 of 1 standardsLevel 3
Work effectively in a team involved in activities for explosive substances and/or articlesInstitute of Commercial Management · covers 1 of 1 standardsLevel 4
Develop your competence in working with explosives, munitions or specified targetsInstitute of Commercial Management · covers 1 of 1 standardsLevel 3
Prepare special effects for a live performancePearson EDI · covers 1 of 1 standardsLevel 2

These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration

Context windows and token limits
Temperature settings for different tasks
RAG (Retrieval Augmented Generation) architectures
Output validation and hallucination detection

What you’ll use

Skills this role draws on

Technical

Hypothesis-Driven Experimentation
Blast Radius Analysis
GameDay Planning & Facilitation
Fault Injection Techniques
Observability-Driven Analysis

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

1
Software Engineer (Backend/Distributed Systems)
2-4 years
Skills to master
- Deep understanding of application logic, inter-service communication, database interactions, and common failure patterns within code. Strong debugging skills.
You're ready to move on when
- You've built and deployed production services that handle significant traffic.
- You've been on-call and experienced real-world production incidents.
- You're curious about why systems fail and how to prevent it, not just fix it.
2
Site Reliability Engineer (SRE) / DevOps Engineer
2-3 years
Skills to master
- Infrastructure as Code, observability tooling, incident response, automation, and a holistic view of system health. Experience with cloud platforms and Kubernetes.
You're ready to move on when
- You've managed and scaled production infrastructure.
- You're comfortable with metrics, logs, and traces to diagnose system issues.
- You're always looking for ways to make systems more resilient and self-healing.
3
Quality Assurance (QA) / Test Automation Engineer (with SRE focus)
3-5 years
Skills to master
- Designing robust test cases, automating complex test scenarios, identifying edge cases, and understanding different types of testing (performance, integration).
You're ready to move on when
- You've built comprehensive test suites for complex applications.
- You're skilled at breaking software in controlled ways to find bugs.
- You're interested in moving beyond functional testing to system-level resilience testing.

11Where this role leads

The long view:Your journey as a Chaos Engineer here is about continuous growth and impact. Whether you want to become a deep technical specialist or eventually lead teams, we're committed to providing the opportunities and support to help you get there. We believe in building careers, not just filling roles.

Pay & demand

Pay and demand for this role will appear here, each figure traced to a named authoritative source (e.g. the ONS Annual Survey of Hours and Earnings, under the Open Government Licence). We don’t show numbers we can’t attribute.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Chaos Engineer is actually changing. In about two minutes, the free confidence check asks where you stand on each of the ten. That's the whole check, and it's what makes the plan yours rather than generic.

12The team that's yours

No two people are taught the same way. This is one-to-one, not one-to-many.

Zavmo is a hyper-personalised AI learning platform. Twelve virtual tutors, each with a different way of teaching, and one orchestration agent that picks the right one for the moment. So every single lesson is shaped around you, your role, and the way you learn. Not a course everyone sits through. A conversation built for you, and no one else.

…and nine more, matched to you after your first chat. Meet all twelve

Start free and meet yours

13What it feels like

A conversation, not a course

Because your tutor knows your role, your projects and your last session, learning sounds like this. And it's different for every single person:

Supervise the set up and operation of special effects for live performancesLevel 3

Applied to your work in Chaos Engineer

This unit aims to provide learners with the knowledge of factors crucial for supervising special effects and the ability to effectively supervise their safe use during live performances.

How the thinking builds

Remember
Understand
Apply
Analyse
Evaluate
Create

An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

One to one, not one to many

No two people run this the same way

A course is written once and handed to everyone. This is assembled around you, and keeps changing as it learns you. Five things it reads, and what each one changes.

Your actual work Every lesson is taught against a live piece of your own work, not a worked example from a textbook.
What you already know The first conversation finds your starting point, so you skip what you can already do and spend the time on what you cannot.
The conditions you learn under Not a learning-styles quiz. The evidence does not support those. The dimensions the research does back, read once and used to shape the plan.
How far you got last time It picks up mid-thought. The tutor knows what you said, what you struggled with, and what it asked you to try.
Which tutor suits the moment Twelve of them, each for a different kind of thinking. The one who walks you through a first idea is not the one who stress-tests it.

See how you learn, free. Eight questions, no sign-up. A directional taster; the diagnostic inside Zavmo goes deeper and keeps adapting.

DemonstrateIllustration

Evidenced on your work in Chaos Engineer

You do not finish by watching something. You finish by showing it on the work you already do, against the measures this job is judged on.

GameDays ExecutedThe number of chaos engineering GameDays you successfully plan and run each quarter.You run six GameDays in Q1, covering three different critical services, each identifying at least one new resilience improvement.> 5 GameDays per quarter
Post-Experiment Report TimelinessHow quickly you get the findings and action items from a GameDay documented and shared.After a GameDay on Tuesday afternoon, the initial report draft is in the shared document by Wednesday morning, ready for review.100% of reports filed within 24 hours of experiment completion
Runbook Adherence & SafetyThe percentage of experiments executed strictly following the agreed-upon runbook, with no unintended 'blast radius' or production impact.You run ten experiments, and in one, a minor deviation from the runbook occurred, but it was quickly corrected with no impact. No production incidents were caused by any of your experiments.> 98% adherence to runbook, 0 production incidents caused by experiments
Identified VulnerabilitiesThe number of unique, critical failure modes or resilience gaps you identify through your experiments.In a GameDay targeting our payment processing service, you discover that a specific network latency scenario causes a deadlock, which was previously unknown.> 1 critical vulnerability identified and documented per GameDay, on average

These are this job's own measures, with its own targets. Nothing is marked evidenced, because nobody has started this yet. Yours would fill in from the work you bring.

Your passport

This isn't a certificate you file away. It's a passport to the life you're designing.

Every credit you earn and every fluency you build adds up: evidence where it counts, carried with you. Zavmo keeps the map: where you are, where you're heading, and the next step, at your pace, around your life. From Chaos Engineer to Senior Chaos Engineer (L3), and whatever you decide comes after.

Level 3 · in progressAI Fluency→ Senior Chaos Engineer (L3)→ your design

Where this takes you

Your journey as a Chaos Engineer here is about continuous growth and impact. Whether you want to become a deep technical specialist or eventually lead teams, we're committed to providing the opportunities and support to help you get there. We believe in building careers, not just filling roles.

See Your Progress GrowIllustration

Chaos Engineer

Hypothesis-Driven Experimentation
Blast Radius Analysis
GameDay Planning & Facilitation
Fault Injection Techniques
Observability-Driven Analysis

This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

14The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Chaos Engineer is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

Senior Chaos Engineer (L3)
2-3 years from this role
You'll move from independently running experiments to designing complex, multi-service scenarios and mentoring junior engineers. You'll own entire workstreams.
- Designing novel fault injection techniques for new technologies or complex interactions.
- Developing and improving internal chaos engineering tooling and frameworks.
- Leading GameDays for critical, high-impact services with wider blast radii.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be honest, parts of chaos engineering can be a bit repetitive or time-consuming. Imagine if you could offload some of that grunt work to AI, freeing you up to focus on the really interesting, complex problems. Well, you can.

AI isn't here to replace the critical thinking of a Chaos Engineer, but it's an incredibly powerful co-pilot. For a mid-level engineer, it means you can punch above your weight, get through more experiments, and generate deeper insights, faster. It's about augmenting your brainpower, not replacing it.

Experiment Scenario Generator

Forget staring at a blank page. AI can analyse past incidents, architectural diagrams, and service dependencies to suggest a prioritised list of high-impact chaos experiments you should run next. It helps you think of failure modes you might have missed, giving you a serious head start.

Automated Anomaly Detection

During a live experiment, AI models can monitor thousands of metrics in real-time, automatically flagging statistically significant deviations from your 'steady state'. This means you'll spot unexpected impacts or subtle issues far faster than any human could, allowing for quicker intervention and deeper learning.

GameDay Report Drafter

After a GameDay, AI can ingest your experiment plan, all that observability data, and even chat logs from Slack, then generate a structured first draft of your post-mortem report. This includes timelines, key observations, and even proposed action items, saving you hours of tedious writing.

Resilience Code Assistant

When an experiment reveals a code-level weakness – say, a missing request timeout – an AI assistant can analyse the relevant codebase and suggest a specific, context-aware code snippet to implement the fix. It's like having an expert pair-programmer who knows all the resilience patterns.

Common questions

How do you become a Chaos Engineer?

Common routes in include Software Engineer (Backend/Distributed Systems) (2-4 years), Site Reliability Engineer (SRE) / DevOps Engineer (2-3 years) and Quality Assurance (QA) / Test Automation Engineer (with SRE focus) (3-5 years). Times vary with prior experience.

Where can a Chaos Engineer progress to?

This role can lead on to Senior Chaos Engineer (L3) (2-3 years from this role), depending on the skills you build.

What level is a Chaos Engineer in the UK?

This role aligns to RQF Level 3 on the UK framework, a guide to the depth of qualification it maps to, not a hard entry bar.

What new skills matter most for a Chaos Engineer?

Increasingly, Prompt Engineering & LLM Integration. These are the areas where the higher-paid, future-proof work is heading.

The honest bit

You’ve started things before

Most of them were built for a room full of people who aren’t you. A cohort moves on whether or not your week allowed it, and by the third week the thing you’re behind on becomes the reason you stop opening it.

There’s no cohort here, and no timetable to fall behind. Before anything starts, Zavmo asks when you’re sharpest and how long you can realistically sit down for, then builds the sessions around those answers. A bad fortnight changes your pace. It doesn’t put you behind.

And you only pay once you start learning. Searching and planning are free, and you can cancel any time — so the cost of finding out is an afternoon, not a year.

What it costs

Less than one coaching session. Every month.

A single career-coaching hour costs more than a month of this, and it ends when the hour does. Zavmo doesn't. It's £70 a month, about £2.30 a day, for a companion that knows a Chaos Engineer, works on the job you actually do, and keeps going at your pace rather than a timetable's.

Searching and planning stay free. You only pay when you start learning.
Your credits are yours. Regulated, and they don't vanish when a subscription ends.
Cancel any time and billing stops. No notice period, no minimum term.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Build my plan, free Here's the first ten minutes: a 2-minute confidence check → your personalised roadmap → meet the tutors matched to you. No card, cancel any time. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.

Chaos Engineer

What's rising in its place

Prompt Engineering & LLM Integration

Skills this role draws on

Technical

How you actually get there, here

Software Engineer (Backend/Distributed Systems)

Site Reliability Engineer (SRE) / DevOps Engineer

Quality Assurance (QA) / Test Automation Engineer (with SRE focus)

The credential is what you can do today. These are what keep you valuable.

Roles this leads to

No two people are taught the same way. This is one-to-one, not one-to-many.

A conversation, not a course

No two people run this the same way

This isn't a certificate you file away. It's a passport to the life you're designing.

Your journey as a Chaos Engineer here is about continuous growth and impact. Whether you want to become a deep technical specialist or eventually lead teams, we're committed to providing the opportunities and support to help you get there. We believe in building careers, not just filling roles.

Everything else the record holds

The career path, and where it branches

Senior Chaos Engineer (L3)

Where AI is starting to help

Experiment Scenario Generator

Automated Anomaly Detection

GameDay Report Drafter

Resilience Code Assistant

Common questions

You’ve started things before

Less than one coaching session. Every month.

You have the map. Walking it is the part we do together.