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Ai Coder Jobs in Phoenix, AZ (NOW HIRING)

Provn

Agentic Software Engineer II

Scottsdale, AZ · On-site

$113K - $178K/yr

Review and validate AI-generated code for correctness, security, and performance before merging * Contribute to refactoring and modernizing existing services and architectures using cloud-native ...

IntraEdge

Gen AI Engineer II

Phoenix, AZ · On-site

$97K - $133K/yr

Utilize GitHub Copilot to assist in writing, debugging, and optimizing code across various programming languages and frameworks. * Integrate Generative AI models into development workflows to ...

Arrivia

Principal Software Engineer - Remote

Scottsdale, AZ · On-site +1

$134K - $180K/yr

You direct AI coding agents through real, multi-step work, decide what becomes shared infrastructure, and make the build-vs-buy calls that shape our roadmap. Operating with broad autonomy and cross ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

Conduct code reviews for AI/ML code with a focus on reproducibility, correctness, and production readiness. * Mentor engineers across the organization in AI engineering fundamentals, LLM integration ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

Conduct code reviews for AI/ML code with a focus on reproducibility, correctness, and production readiness. * Mentor engineers across the organization in AI engineering fundamentals, LLM integration ...

Worky

Agentic Software Engineer III

Scottsdale, AZ · On-site

$120 - $170/hr

Guard code quality: Review and validate AI-generated code for correctness, security, performance, and maintainability, helping set quality standards across the team. * Modernize the platform:

McCarthy Holdings, Inc.

AI Engineer II

Phoenix, AZ · On-site

$110 - $170/hr

Leverage AI-assisted development tools and coding copilots to accelerate delivery while maintaining high standards for code quality, testing, security, and maintainability. * Participate in MLOps and ...

FHLB Des Moines

Engineer II- Software

Chandler, AZ · On-site

$90 - $140/hr

Utilize AI-powered development tools such as Claude and GitHub Copilot to accelerate coding, debugging, documentation, and problem-solving. * Collaborate with cross-functional teams including product ...

NewReach Education

Martech Platform Builder

Tempe, AZ · On-site

$105K/yr

Use AI coding tools such as Cursor and Claude to rapidly build, troubleshoot, and improve marketing technology. * Build and maintain AI/agentic workflows, MCP tools, skills, and playbooks that ...

McCarthy Holdings, Inc.

AI Engineer II

Phoenix, AZ · On-site

$88K - $121K/yr

Leverage AI-assisted development tools and coding copilots to accelerate delivery while maintaining high standards for code quality, testing, security, and maintainability. * Participate in MLOps and ...

McCarthy Holdings, Inc.

AI Engineer II

Phoenix, AZ · On-site

$88K - $121K/yr

Leverage AI-assisted development tools and coding copilots to accelerate delivery while maintaining high standards for code quality, testing, security, and maintainability. * Participate in MLOps and ...

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All JobsAi Coder JobsAi Coder Jobs in Phoenix, AZ

Ai Coder information

See Phoenix, AZ salary details

$15

$27

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How much do ai coder jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for ai coder in Phoenix, AZ is $27.30, according to ZipRecruiter salary data. Most workers in this role earn between $18.85 and $34.38 per hour, depending on experience, location, and employer.

What is an AI coder?

AI Coders are professionals who develop, implement, and maintain artificial intelligence (AI) systems and applications. They use programming languages such as Python, Java, and R to write code that enables machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. AI Coders often work with machine learning models, neural networks, and large datasets to create intelligent solutions for various industries. Their work can range from building chatbots and recommendation systems to designing complex algorithms for automation.

What types of projects do AI coders typically work on, and how does project collaboration usually happen?

AI Coders are often involved in developing machine learning models, creating data pipelines, and integrating AI solutions into existing products. Collaboration is a key part of the role, with AI Coders working closely with data scientists, software engineers, and product managers to translate business needs into technical solutions. Most teams use agile methodologies, daily stand-ups, and collaborative platforms like GitHub or Jira to coordinate tasks and track progress. This structure ensures that AI Coders receive frequent feedback and can contribute ideas throughout the development cycle.

What are the key skills and qualifications needed to thrive as an AI coder, and why are they important?

To thrive as an AI Coder, you need strong programming skills (especially in Python), a solid understanding of machine learning concepts, and typically a degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, as well as experience with version control systems such as Git, is essential. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with teams and explain complex solutions. These skills and qualities are crucial for developing, optimizing, and maintaining reliable AI models that address real-world challenges.

What is the difference between Ai Coder vs Data Scientist?

AspectAi CoderData Scientist
Required CredentialsProgramming skills, knowledge of AI frameworks, certifications in AI/MLStatistics, programming, data analysis certifications
Work EnvironmentSoftware development teams, AI research labsData analysis teams, research environments
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles involve working with data and algorithms, Ai Coders primarily focus on developing AI models and coding AI solutions, whereas Data Scientists analyze data to extract insights and inform business decisions. Ai Coders are more involved in software development, while Data Scientists emphasize statistical analysis and data interpretation.

How do you become an AI coder?

To become an AI coder, you typically need a strong foundation in programming languages such as Python or Java, along with knowledge of machine learning frameworks like TensorFlow or PyTorch. Earning a degree in computer science, data science, or a related field and gaining experience through projects or internships are common steps. Developing skills in algorithms, data structures, and mathematics is also essential for working effectively in AI development.

How much do AI coders make?

AI coders, also known as artificial intelligence programmers, typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can earn higher salaries, especially in tech hubs or large companies.

What are popular job titles related to Ai Coder jobs in Phoenix, AZ?

For Ai Coder jobs in Phoenix, AZ, the most frequently searched job titles are:

What job categories do people searching Ai Coder jobs in Phoenix, AZ look for?

The top searched job categories for Ai Coder jobs in Phoenix, AZ are:

What cities near Phoenix, AZ are hiring for Ai Coder jobs?

Cities near Phoenix, AZ with the most Ai Coder job openings:

Ai Coder jobs near you
Infographic showing various Ai Coder job openings in Phoenix, AZ as of August 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 70% Physical, 4% Hybrid, and 26% Remote job distribution, with an average salary of $53,962 per year, or $25.9 per hour.

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Chandler, AZ • On-site

$20 - $30/hr

Full-time

Posted 2 days ago

New

Job description

Type: Contract, hourly

Location: Remote

Hours: 20–30 per week

Pay: $20–30/hour, based on experience and language coverage

Start: Immediate

ABOUT THE ROLE

We evaluate how well advanced AI coding agents solve real engineering problems. An agent is given a real open source codebase inside a container and a hard task, then works on its own for 80 to 250 steps. A trajectory is the full record of that run — every command, result, and decision.

You will do two jobs, and you should expect either on any given day.

•Annotate — Read a trajectory nobody has looked at yet and judge it step by step.

• Review — Take an existing annotation, written by our AI tooling or another person, and confirm, correct, or reject it.

TASKS YOU'LL SEE

• Feature build — Add a working feature to a live library without breaking anything that already worked.

• Rebuild — Work out what a compiled tool does by running it, then rebuild it to match its output, exit codes, and file effects.

• Bug hunt — Find and fix twenty undocumented bugs across a dozen files with no test suite, then record what caused them.

Mostly Python and Go, with some Rust, C, and Ct+. A trajectory runs about 100 steps.

WHAT YOU JUDGE IN A TRAJECTORY

• Was the command right for the state the environment was actually in?

• Did the agent read the previous output correctly?

• Was the step wrong, or only inefficient — these are scored differently.

• Where did the run first go off course — usually earlier than where it visibly broke.

• Did the agent notice its own mistake and recover, or keep building on a false assumption?

• Did it game the grader instead of solving the task (e.g., weakening a test or hardcoding an expected value)?

WHAT WE NEED FROM YOU

• Experience — 2+ years in software engineering, DevOps, or site reliability, with real debugging in real codebases.

• Languages — Strong in Python or Go, and able to read a language you've never used.

• Linux — Comfortable with logs, running processes, build failures, and containers.

• Workflow — Everyday Git, diffs, pull requests, and issue tracking.

• Debugging — Able to work with no test suite and no error message pointing at the cause.

• Focus — Able to hold context across a long run, because step 74 can depend on step 12.

• Writing — Clear English, since every judgement needs an explanation another engineer can check.

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