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AI Deployment Strategist Test

The AI Deployment Strategist Test evaluates a candidate's expertise in deploying AI applications effectively. It assesses knowledge in prompt engineering, generative AI, Docker, Linux operations, and Python programming. The test includes MCQs for core concepts and coding challenges for technical roles, testing the ability to strategize and implement AI-driven systems.

Covered skills:

  • Prompt Engineering
  • Generative AI
  • Docker
  • Linux
  • Python Programming
  • DevOps
  • Backend Development
  • System Design
  • AI Deployment Strategies
  • Cloud Services
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About the AI Deployment Strategist Assessment Test


The AI Deployment Strategist Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

  • Ability to craft effective and precise prompts for AI models.
  • Understanding of the underlying mechanisms of generative AI systems.
  • Proficiency in containerizing applications using Docker.
  • Skill in navigating and managing Linux systems efficiently.
  • Competence in writing clean and efficient Python code.
  • Capability to implement continuous integration and continuous delivery pipelines.
  • Understanding of backend development principles and frameworks.
  • Ability to design scalable and efficient system architectures.
  • Skill in deploying AI models to production with best practices.
  • Familiarity with cloud service providers and their deployment mechanisms.

1200+ customers in 80 countries


Use Adaface tests trusted by recruitment teams globally. Adaface skill assessments measure on-the-job skills of candidates, providing employers with an accurate tool for screening potential hires.

customers in 75 countries
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Non-googleable questions


We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 15,000+ questions. The actual questions on this AI Deployment Strategist Test will be non-googleable.

🧐 Question

Easy

JSON Prompt Design
JSON structure
Prompt crafting
Data types
Solve
You are asked to create a prompt for a language model that outputs JSON data for a company's employee database. The JSON must include an employee's ID, name, age, and whether they are currently active. Consider how you might structure your prompt given these fields. Identify the best prompt design.
Example JSON output:
{
   "ID": "123",
   "Name": "John Doe",
   "Age": 30,
   "Active": true
}
Which prompt structure would most effectively guide the language model to generate the correct JSON format?
A: Create JSON objects for employees with fields: ID, Name, Age, Active. ID should be a string.
B: Generate JSON data: ID, Name, Age, Active. ID is a number.
C: Output JSON: ID (string), Name, Age (integer), Active (boolean).
D: Make JSON: ID, Name, Age, Active. ID is always number.
E: Design JSON response: ID, Name, Age, Active with clear typing.
F: Provide JSON example: Employee data with structured fields.

Medium

Temperature Settings
Temperature calibration
Generative behavior
Output variability analysis
Solve
Consider the following prompt given to an LLM:

System Prompt: "You are a creative writing assistant helping authors develop character descriptions. Use vivid imagery and engaging language to bring characters to life."
Main Prompt: "Write a character description for a mysterious librarian with the following traits:

Works in an ancient library
Has silver hair and green eyes
Knows secrets about forbidden books
Appears to be in their 40s but seems much older
Always wears a pendant with strange symbols"

Three outputs were generated with different temperature settings:
Output A:
"The librarian possesses silver hair and green eyes. Age appears to be approximately 40 years. Works in an ancient library facility. Has knowledge of restricted book collections. Wears jewelry featuring symbolic markings. Maintains professional demeanor while handling library materials."
Output B:
"Elara moves through the ancient library like a ghost haunting familiar halls, her silver hair catching moonbeams that slip through Gothic windows. Those emerald eyes hold centuries of secrets—too many secrets for someone who claims only four decades of life. The obsidian pendant at her throat pulses with runes that predate any known language, and when she speaks of the forbidden texts, her voice carries the weight of ages. There's something unsettling about how she never seems surprised by anything, as if she's been waiting lifetimes for each visitor to find their way to her domain."
Output C:
"Meet Elara, the enigmatic keeper of knowledge whose silver locks frame a face that defies time itself. Her piercing green eyes seem to peer directly into your soul, holding secrets that could unravel reality. The ancient library around her creaks with whispered stories, and she alone holds the keys to the forbidden sections where dangerous truths slumber. The mystical pendant adorning her neck bears symbols older than civilization, pulsing with otherworldly energy that hints at her true nature."
Which temperature setting was most likely used for each output?
A) Output A (T=0.1), Output B (T=1.0), Output C (T=0.5)
B) Output A (T=0.5), Output B (T=0.1), Output C (T=1.0)
C) Output A (T=0.1), Output B (T=0.5), Output C (T=1.0)
D) Output A (T=1.0), Output B (T=0.5), Output C (T=0.1)
E) Output A (T=0.5), Output B (T=1.0), Output C (T=0.1)

Medium

Docker Multistage Build Analysis
Multistage Builds
Optimization
Dockerfile Syntax
Solve
Consider the following Dockerfile, which utilizes multistage builds. The aim is to build a lightweight, optimized image that just runs the application.
 image
The Dockerfile first defines a base image that includes Node.js and npm, then it creates an intermediate image to install the npm dependencies. Afterwards, it runs the tests in another stage and finally, creates the release image.

Which of the following statements are true?

A: The final image will include the test scripts.
B: If a test fails, the final image will not be created.
C: The node_modules directory in the final image comes from the base image.
D: The final image will only contain the necessary application files and dependencies.
E: If the application's source code changes, only the release stage needs to be rebuilt.

Easy

Docker Networking and Volume Mounting Interplay
Networking
Volume Mounting
Docker Networking
Solve
You have two docker containers, X and Y. Container X is running a web service listening on port 8080, and container Y is supposed to consume this service. Both containers are created from images that don't have any special network configurations.

Container X has a Dockerfile as follows:
 image
And, you build and run it with the following commands:
 image
Container Y is also running alpine with python installed, and it's supposed to read data from the `/app/data` directory and send a GET request to `http://localhost:8080` every 5 minutes. The Dockerfile for container B is:
 image
And you run it with:
 image
Assuming all the python scripts work perfectly and firewall isn't blocking any connections, you find that container Y can't access the web service of container X via `http://localhost:8080` and also it can't read the data in `/app/data` directory. What could be the potential reason(s)?
A: Y can't access X's web service because they're in different Docker networks.
B: Y can't read the data because the volume is not shared correctly.
C: Both A and B are correct.
D: Both A and B are incorrect.

Medium

Dockerfile Optimization
Dockerfile
Multi-stage builds
Layer Caching
Solve
You have been asked to optimize a Dockerfile for a Python application that involves a heavy dependency installation. Here is the Dockerfile you are starting with:
 image
Given that the application's source code changes frequently but the dependencies listed in requirements.txt rarely change, how can you optimize this Dockerfile to take advantage of Docker's layer caching, reducing the build time?
A: Move the `RUN pip install` command to before the `COPY` command.
B: Change `COPY . /app` to `COPY ./app.py /app` and move the `RUN pip install` command to before the `COPY` command.
C: Add `RUN pip cache purge` before `RUN pip install`.
D: Replace the base image with `python:3.8-slim`.
E: Implement multi-stage builds.

Medium

Dockerfile Updates
Cache
Docker Cache Strategies
Solve
Check the following Dockerfile used for a project (STAGE 1):
 image
We created an image from this Dockerfile on Dec 14 2021. A couple of weeks after Dec 14 2021, Ubuntu released new security updates to their repository. After 2 months, we modified the file (STAGE 2):
 image
Couple of weeks later, we further modified the file to add a local file ada.txt to /ada.txt (STAGE 3): (Note that ada.txt exists in /home/adaface and the dockerfile exists in /home/code folders)
 image
Pick correct statements:

A: If we run “docker build .” at STAGE 2, new Ubuntu updates will be fetched because apt-get update will be run again since cache is invalidated for all lines/layers of Dockerfile when a new line is added.
B: If we run “docker build .” at STAGE 2, new Ubuntu updates will not be fetched since cache is invalidated only for last two lines of the updated Dockerfile. Since the first two commands remain the same, cached layers are re-used skipping apt get update.
C: To skip Cache, “docker build -no-cache .” can be used at STAGE 2. This will ensure new Ubuntu updates are picked up.
D: Docker command “docker build .” at STAGE 3 works as expected and adds local file ada.txt to the image.
E: Docker command “docker build .” at STAGE 3 gives an error “no such file or directory” since /home/adaface/ada.txt is not part of the Dockerfile context.

Medium

Efficient Dockerfile
Dockerfile
Dockerfile Syntax
Containerization
Resource Optimization
Solve
Review the following Dockerfiles that work on two projects (project and project2):
 image
All Docker files have the same end result:

- ‘project’ is cloned from git. After running few commands, ‘project’ code is removed.
- ‘project2’ is copied from file system and permissions to the folder is changed.
Pick the correct statements:

A: File 1 is the most efficient of all.
B: File 2 is the most efficient of all.
C: File 3 is the most efficient of all.
D: File 4 is the most efficient of all.
E: Merging multiple RUN commands into a single RUN command is efficient for ‘project’ since each RUN command creates a new layer with changed files and folders. Deleting files with RUN only marks these files as deleted but does not reclaim disk space. 
F: Copying ‘project2’ files and changing ownership in two separate commands will result in two layers since Docker duplicates all the files twice.

Medium

Debugging Issues
Environment Variables
Debugging
System Administration
Command Line Interface
Solve
You are working on a Linux system and have recently installed a new program named myprogram. The executable is located in /opt/myprogram/bin/. You want to be able to run this program from any directory in your shell without specifying the full path.
You executed the following command:
export PATH="/opt/myprogram/bin"
However, when you try to run the program using myprogram, you get the following error message:
-bash: myprogram: command not found

Which of the following commands can fix this issue and allow you to run the program?
A: export PATH=$PATH:/opt/myprogram/bin/
B: export PATH="/opt/myprogram:$PATH"
C: export PATH="/opt/myprogram/bin:$PATH"
D: ln -s /opt/myprogram/bin/myprogram /usr/local/bin/myprogram

Easy

File Structure and Navigation
Files
Basic Commands
File System Management
Directory Structure Manipulation
Solve
Consider the following directory structure:
 image
You start at /home/user and execute the following commands:
 image
What will be the resulting directory structure?
 image

Medium

Fork mellow yellow
Solve
How many times will the following code will print "Mellow Yellow"?
 image

Medium

Remote server connection
SSH
Ssh
Port Forwarding
Solve
Our software engineering intern, Wu is looking to use port 4545 on localhost to connect to a remote server called woot.bananas.com on port 80. Which command would you recommend for this?
 image

Medium

ZeroDivisionError and IndexError
Exceptions
Exception Handling
Error Handling
Solve
What will the following Python code output?
 image

Medium

Session
File Handling
Dictionary
Csv Parsing
Exception Handling In File Input/output
Solve
 image
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file:
Tony,10
Stark,12
Black,25
Your program should ignore a non-conforming line like this one.
Stark,3
Widow,6
Widow,14
The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 }
What should replace the CODE TO FILL line to complete the function?
 image

Medium

Max Code
Arrays
Code Analysis
Algorithm Understanding
Solve
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
 image

Medium

Recursive Function
Recursion
Dictionary
Lists
Solve
Consider the following Python code:
 image
In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None.

nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target.

What will the output be after executing the above code?

Medium

Stacking problem
Stack
Linkedlist
Solve
What does the below function ‘fun’ does?
 image
A: Sum of digits of the number passed to fun.
B: Number of digits of the number passed to fun.
C: 0 if the number passed to fun is divisible by 10. 1 otherwise.
D: Sum of all digits number passed to fun except for the last digit.

Medium

Resource Analysis
Process Management
System Performance
Log Analysis
Solve
As a senior DevOps engineer, you are tasked with diagnosing performance issues on a Linux server running Ubuntu 20.04. The server hosts several critical applications, but lately, users have been experiencing significant slowness. Initial monitoring shows that CPU and memory utilization are consistently high. To identify the root cause, you check the output of `top` and `ps` commands, which indicate that a particular process is consuming an unusually high amount of resources. However, the process name is generic and does not clearly indicate which application or service it belongs to. You also examine `/var/log/syslog` for any unusual entries but find nothing out of the ordinary. Based on this situation, which of the following steps would most effectively help you identify and resolve the performance issue?
A: Increase the server's physical memory and CPU capacity.
B: Use the `lsof` command to identify the files opened by the suspect process.
C: Reboot the server to reset all processes.
D: Examine the `/etc/hosts` file for any incorrect configurations.
E: Run the `netstat` command to check for abnormal network activity.
F: Check the crontab for any recently added scheduled tasks.

Medium

Streamlined DevOps
Continuous Integration
Scripting
Git
Shell Scripting
Solve
You are in charge of developing a Bash script for setting up a continuous integration pipeline for a web application. The source code is hosted in a Git repository. The script's goals include:

1. Ensuring the local copy of the repository in /var/www/html is updated to the latest version.
2. Creating a .env file with APP_ENV=production in the project root if it doesn't already exist.
3. Running a test suite with ./run_tests.sh and handling any test failures appropriately.
4. Logging the current timestamp and commit hash in deployment_log.txt in the project root if tests pass.

Which of the following script options would most effectively and safely accomplish these tasks?
 image

Medium

Broker Replication
System Design
Distributed Systems
Message Processing
Fault Tolerance
Solve
You are working on a large-scale, distributed, and fault-tolerant message processing system designed to handle high throughput and low latency requirements. The system is based on the publish-subscribe pattern and uses multiple brokers to distribute messages across various topics and partitions. In this architecture, both publishers and subscribers are considered clients. The brokers are responsible for replicating messages among themselves to ensure fault tolerance and data durability.
 image
A client reports successfully publishing a message on a specific topic. However, one of the subscribers has not received the message. To investigate the issue, you have gathered detailed logs and system design data, as shown below:
 image
Based on the information provided, which of the following is the most likely reason for the issue?

A: The message was not published on the topic
B: Client C is not subscribed to the correct topic
C: There is a replication lag between brokers B1 and B2
D: Client C is consuming from the wrong broker
E: The message processing system failed to acknowledge the message

Medium

Load Balancer Latency
Debugging
Troubleshooting
Resource Management
Performance Tuning
Solve
A backend service is experiencing intermittent latency spikes while processing incoming requests. The service is deployed in a multi-node environment with a load balancer in front. You suspect that the issue might be related to resource contention. You collect the following performance metrics from the affected nodes during a spike:
 image
Which of the following is the most probable cause of the latency spikes?
A: High memory usage on the affected nodes.
B: Disk I/O bottlenecks on the affected nodes.
C: Insufficient CPU resources on the affected nodes.
D: Uneven distribution of incoming requests by the load balancer.
E: Network latency between the load balancer and the backend nodes.

Medium

Optimal Data Replication and Consistency in Distributed Systems
Data Consistency
Load Balancing
Fault Tolerance
Solve
Consider a distributed e-commerce platform designed to handle high traffic volumes and ensure data consistency across its services. The platform uses a distributed database that replicates data across multiple nodes to increase availability and performance. To balance the load, it employs a load balancer that distributes user requests evenly across these nodes. The system is designed to tolerate the failure of up to two nodes without affecting the platform's overall availability.

Given the critical requirement for strong consistency to prevent issues such as overselling of products, the system uses a consensus algorithm for replication. The database is configured with a replication factor of 5, meaning each piece of data is stored on 5 nodes. For read and write operations to be considered successful, they must be acknowledged by a majority of the nodes involved in the operation.

Assuming all nodes have equal hardware resources and network latency between nodes is negligible, which of the following configurations would best meet the platform's requirements for high availability, performance, and strong consistency?
A: Reads require acknowledgment from 2 nodes, and writes require acknowledgment from 4 nodes.
B: Reads and writes both require acknowledgment from 3 nodes.
C: Reads require acknowledgment from 3 nodes, and writes require acknowledgment from 2 nodes.
D: Reads and writes both require acknowledgment from 4 nodes.
E: Reads require acknowledgment from 1 node, and writes require acknowledgment from 5 nodes.
F: Reads and writes both require acknowledgment from 5 nodes.

Easy

Real-time Vehicle Tracking for Logistics Company
Data Storage
Scalability
Real-time Updates
NoSQL
Solve
TransitTrack is a logistics company that needs to store real-time location data (latitude, longitude) of their vehicles as they move across the city. The system should be optimized for fast read and write operations to provide real-time tracking. TransitTrack can tolerate occasional data loss since the vehicle locations are updated frequently. Which of the following data storage solutions should TransitTrack implement for their vehicle tracking system?
A: Utilize a relational database management system (RDBMS) like PostgreSQL with a table indexed on the vehicle_id column for efficient data insertion and retrieval.
B: Implement an in-memory cache like Redis to store the vehicle location data, with the vehicle_id as the key and the latitude-longitude pair as the value.
C: Use a document-oriented database like MongoDB to store the vehicle location data as GeoJSON documents, enabling geospatial querying capabilities.
D: Develop a custom in-memory data structure using a spatial indexing technique like an R-tree to store and query the vehicle location data efficiently.
E: Use a time-series database like InfluxDB to store the vehicle location data along with timestamps, allowing for efficient querying and analysis of historical location data.

Medium

Session stickiness with ELB
Cookies
Elb Configuration
Load Balancing
Sticky Sessions
Solve
Johnny Bravo is setting up a new e-commerce store for men's clothing. He set up session stickiness with ELB. But he does not want ELB to manage the cookie, he wants the application to manage the cookie. When the server instance, which is bound to a cookie, crashes what do you expect will happen?
A: ELB will throw an error due to cookie unavailability
B: The response will have a cookie but stickiness will be deleted
C: The session will be sticky and ELB will route requests to another server as ELB keeps replicating the Cookie
D: The session will not be sticky until a new cookie is inserted

Medium

Updating UI after Encoding
UI Design
Decoupling
Async/await
Concurrency
Solve
Imagine you’re a developer at Songbird Inc, working on a music editing app for mobile devices. The app allows users to edit audio clips and export them in various audio formats. Once a user finishes editing a clip, they can choose an output format and initiate the encoding process. This encoding process can take a while depending on the chosen format and the length of the clip. Because it’s a mobile app, you want to avoid freezing the UI while encoding is in progress.

What’s the most appropriate approach to notify the user when the encoding is complete and the exported file is ready?
A: Directly modify the UI elements from within the encoding logic. When encoding finishes, the encoding system can directly tell the UI components to update themselves with the new information (e.g., change a button text to “Export Complete”).
B: Separate the UI update logic from the encoding process. The encoding system should trigger a custom event (e.g., “EncodingFinishedEvent”) upon completion. UI components can listen for this event and update themselves accordingly when it’s received.
C:  Have the UI code continuously check on the encoding status with a loop (often referred to as busy waiting or polling). The loop would keep checking a flag or variable set by the encoding system until the encoding is complete. Once complete, the UI can update itself.
D:  Introduce a central message queue or event bus. The encoding system can publish a message to the message queue upon finishing the task. Separate UI update logic would be subscribed to the queue, listening for relevant messages. When it receives the message about encoding completion, it can update the UI.
E: Let the encoding logic return a callback function to the UI layer when it’s initiated. Once encoding is finished, the encoding system calls back this function, allowing the UI to update itself.
🧐 Question 🔧 Skill

Easy

JSON Prompt Design
JSON structure
Prompt crafting
Data types

2 mins

Prompt Engineering
Solve

Medium

Temperature Settings
Temperature calibration
Generative behavior
Output variability analysis

2 mins

Prompt Engineering
Solve

Medium

Docker Multistage Build Analysis
Multistage Builds
Optimization
Dockerfile Syntax

3 mins

Docker
Solve

Easy

Docker Networking and Volume Mounting Interplay
Networking
Volume Mounting
Docker Networking

3 mins

Docker
Solve

Medium

Dockerfile Optimization
Dockerfile
Multi-stage builds
Layer Caching

2 mins

Docker
Solve

Medium

Dockerfile Updates
Cache
Docker Cache Strategies

2 mins

Docker
Solve

Medium

Efficient Dockerfile
Dockerfile
Dockerfile Syntax
Containerization
Resource Optimization

2 mins

Docker
Solve

Medium

Debugging Issues
Environment Variables
Debugging
System Administration
Command Line Interface

2 mins

Linux
Solve

Easy

File Structure and Navigation
Files
Basic Commands
File System Management
Directory Structure Manipulation

2 mins

Linux
Solve

Medium

Fork mellow yellow

2 mins

Linux
Solve

Medium

Remote server connection
SSH
Ssh
Port Forwarding

2 mins

Linux
Solve

Medium

ZeroDivisionError and IndexError
Exceptions
Exception Handling
Error Handling

2 mins

Python
Solve

Medium

Session
File Handling
Dictionary
Csv Parsing
Exception Handling In File Input/output

2 mins

Python
Solve

Medium

Max Code
Arrays
Code Analysis
Algorithm Understanding

2 mins

Python
Solve

Medium

Recursive Function
Recursion
Dictionary
Lists

3 mins

Python
Solve

Medium

Stacking problem
Stack
Linkedlist

4 mins

Python
Solve

Medium

Resource Analysis
Process Management
System Performance
Log Analysis

3 mins

DevOps
Solve

Medium

Streamlined DevOps
Continuous Integration
Scripting
Git
Shell Scripting

2 mins

DevOps
Solve

Medium

Broker Replication
System Design
Distributed Systems
Message Processing
Fault Tolerance

3 mins

Backend
Solve

Medium

Load Balancer Latency
Debugging
Troubleshooting
Resource Management
Performance Tuning

3 mins

Backend
Solve

Medium

Optimal Data Replication and Consistency in Distributed Systems
Data Consistency
Load Balancing
Fault Tolerance

2 mins

System Design
Solve

Easy

Real-time Vehicle Tracking for Logistics Company
Data Storage
Scalability
Real-time Updates
NoSQL

2 mins

System Design
Solve

Medium

Session stickiness with ELB
Cookies
Elb Configuration
Load Balancing
Sticky Sessions

2 mins

System Design
Solve

Medium

Updating UI after Encoding
UI Design
Decoupling
Async/await
Concurrency

2 mins

System Design
Solve
🧐 Question 🔧 Skill 💪 Difficulty ⌛ Time
JSON Prompt Design
JSON structure
Prompt crafting
Data types
Prompt Engineering
Easy 2 mins
Solve
Temperature Settings
Temperature calibration
Generative behavior
Output variability analysis
Prompt Engineering
Medium 2 mins
Solve
Docker Multistage Build Analysis
Multistage Builds
Optimization
Dockerfile Syntax
Docker
Medium 3 mins
Solve
Docker Networking and Volume Mounting Interplay
Networking
Volume Mounting
Docker Networking
Docker
Easy 3 mins
Solve
Dockerfile Optimization
Dockerfile
Multi-stage builds
Layer Caching
Docker
Medium 2 mins
Solve
Dockerfile Updates
Cache
Docker Cache Strategies
Docker
Medium 2 mins
Solve
Efficient Dockerfile
Dockerfile
Dockerfile Syntax
Containerization
Resource Optimization
Docker
Medium 2 mins
Solve
Debugging Issues
Environment Variables
Debugging
System Administration
Command Line Interface
Linux
Medium 2 mins
Solve
File Structure and Navigation
Files
Basic Commands
File System Management
Directory Structure Manipulation
Linux
Easy 2 mins
Solve
Fork mellow yellow
Linux
Medium 2 mins
Solve
Remote server connection
SSH
Ssh
Port Forwarding
Linux
Medium 2 mins
Solve
ZeroDivisionError and IndexError
Exceptions
Exception Handling
Error Handling
Python
Medium 2 mins
Solve
Session
File Handling
Dictionary
Csv Parsing
Exception Handling In File Input/output
Python
Medium 2 mins
Solve
Max Code
Arrays
Code Analysis
Algorithm Understanding
Python
Medium 2 mins
Solve
Recursive Function
Recursion
Dictionary
Lists
Python
Medium 3 mins
Solve
Stacking problem
Stack
Linkedlist
Python
Medium 4 mins
Solve
Resource Analysis
Process Management
System Performance
Log Analysis
DevOps
Medium 3 mins
Solve
Streamlined DevOps
Continuous Integration
Scripting
Git
Shell Scripting
DevOps
Medium 2 mins
Solve
Broker Replication
System Design
Distributed Systems
Message Processing
Fault Tolerance
Backend
Medium 3 mins
Solve
Load Balancer Latency
Debugging
Troubleshooting
Resource Management
Performance Tuning
Backend
Medium 3 mins
Solve
Optimal Data Replication and Consistency in Distributed Systems
Data Consistency
Load Balancing
Fault Tolerance
System Design
Medium 2 mins
Solve
Real-time Vehicle Tracking for Logistics Company
Data Storage
Scalability
Real-time Updates
NoSQL
System Design
Easy 2 mins
Solve
Session stickiness with ELB
Cookies
Elb Configuration
Load Balancing
Sticky Sessions
System Design
Medium 2 mins
Solve
Updating UI after Encoding
UI Design
Decoupling
Async/await
Concurrency
System Design
Medium 2 mins
Solve
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Preview questions
love bonito

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!

Brandon Lee, Head of People, Love, Bonito

Brandon
love bonito

It's very easy to share assessments with candidates and for candidates to use. We get good feedback from candidates about completing the tests. Adaface are very responsive and friendly to deal with.

Kirsty Wood, Human Resources, WillyWeather

Brandon
love bonito

We were able to close 106 positions in a record time of 45 days! Adaface enables us to conduct aptitude and psychometric assessments seamlessly. My hiring managers have never been happier with the quality of candidates shortlisted.

Amit Kataria, CHRO, Hanu

Brandon
love bonito

We evaluated several of their competitors and found Adaface to be the most compelling. Great library of questions that are designed to test for fit rather than memorization of algorithms.

Swayam Narain, CTO, Affable

Brandon

Why you should use Pre-employment AI Deployment Strategist Test?

The AI Deployment Strategist Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

  • Constructing effective AI prompts.
  • Understanding machine learning model outputs.
  • Deploying applications using Docker containers.
  • Executing Linux command-line operations.
  • Writing efficient Python code.
  • Automating tasks with DevOps tools.
  • Building RESTful backend services.
  • Designing scalable system architectures.
  • Implementing cloud-based AI solutions.
  • Optimizing generative AI algorithms.

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the AI Deployment Strategist Test?

Prompt Engineering: Prompt engineering involves crafting and refining inputs for AI models to yield optimal outputs. It's crucial for extracting accurate and relevant results from generative models, forming a core part of AI applications and strategies.

Generative AI: Generative AI refers to systems that can create new content, such as text, images, or code, using complex algorithms. Understanding this skill is vital for deploying AI solutions that require content creation and innovation.

Docker: Docker is a containerization technology for automating the deployment of applications. Measuring this skill ensures proficiency in building scalable and isolated computing environments for AI applications.

Linux: Linux is a fundamental operating system for server environments and is integral for backend and cloud-based AI deployments. Mastery of Linux is essential for efficient system administration and automation in AI setups.

Python Programming: Python is the primary language for AI and machine learning development, renowned for its simplicity and vast resources. Testing this skill ensures the ability to implement algorithms and manage AI frameworks effectively.

DevOps: DevOps covers practices that combine software development and IT operations, aiming for shorter development cycles and reliable releases. Proficiency in DevOps is key to automating and streamlining AI deployment processes.

Backend Development: Backend development involves building and maintaining the server-side of applications where data processing and logic occur. Assessing skills in this area guarantees robust, secure, and efficient handling of AI data workflows.

System Design: System design entails creating architectures that support the scalability and performance of applications. It's necessary for developing AI systems that are resilient and can handle complex operations.

AI Deployment Strategies: AI deployment strategies focus on the best methodologies to integrate AI models into production environments. Evaluating this skill ensures the effective implementation and monitoring of AI solutions in real-world scenarios.

Cloud Services: Cloud services provide on-demand computing resources and are essential for scalable and cost-effective AI deployments. Knowledge of cloud environments is critical for deploying flexible and robust AI applications.

Full list of covered topics

The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for AI Deployment Strategist Test to be based on.

Prompt Crafting
Prompt Optimization
Transformer Models
Neural Networks
Docker Compose
Docker Networking
Docker Security
Linux Shell
Linux Permissions
Linux Networking
Python Syntax
Python Libraries
CI/CD
Jenkins Pipelines
Kubernetes
API Development
RESTful Services
Microservices
Load Balancing
Scalability
AWS EC2
Azure Functions
Hybrid Cloud
Model Deployment
Continuous Deployment
Version Control
Git Commands
Git Branching
Data Security
System Monitoring
Error Handling
Container Orchestration
Infrastructure as Code
Cloud Security

What roles can I use the AI Deployment Strategist Test for?

  • AI Deployment Strategist
  • DevOps Engineer
  • Backend Developer
  • AI Engineer
  • Cloud Architect
  • Machine Learning Engineer
  • Data Engineer
  • Solution Architect
  • Systems Engineer
  • Python Developer

How is the AI Deployment Strategist Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

  • Applying advanced prompt engineering techniques.
  • Managing large-scale containerized applications.
  • Configuring and securing Linux environments.
  • Developing high-performance Python applications.
  • Integrating continuous integration/continuous deployment pipelines.
  • Architecting complex backend systems.
  • Designing robust system interfaces.
  • Utilizing cloud services for AI deployment.
  • Ensuring scalability and reliability in systems.
  • Enhancing AI models with data engineering.

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Have questions about the AI Deployment Strategist Hiring Test?

What is AI Deployment Strategist Test?

The AI Deployment Strategist Test is designed to evaluate a candidate's proficiency in deploying AI solutions effectively. Organizations use it to identify experts who can manage large-scale AI deployments and ensure optimal performance.

Can I combine AI Deployment Strategist Test with Generative AI questions?

Yes, recruiters can request a custom test that includes Generative AI questions along with the AI Deployment Strategist Test. Check out our Working with Generative AI Test for more details on how we assess this skill.

How are senior roles assessed in the AI Deployment Strategist Test?

Senior roles are assessed through scenarios involving advanced prompt engineering techniques, managing large-scale containerized applications, configuring Linux environments, and ensuring system scalability and reliability.

How to use the AI Deployment Strategist Test in my hiring process?

Use this test as a pre-screening tool at the beginning of your recruitment. Share a link in your job post or invite candidates directly. It helps to identify skilled candidates faster.

What are the main AI tests?
Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

  • Hidden AI Tools Detection with Honestly
  • Non-googleable questions
  • IP proctoring
  • Screen proctoring
  • Web proctoring
  • Webcam proctoring
  • Plagiarism detection
  • Secure browser
  • Copy paste protection

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.

I'm a candidate. Can I try a practice test?

No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

What is the cost of using this test?

You can check out our pricing plans.

Can I get a free trial?

Yes, you can sign up for free and preview this test.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

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Along with scorecards that report the performance of the candidate in detail, you also receive a comparative analysis against the company average and industry standards.

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