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Freelance Backend Python Jobs in Phoenix, AZ (NOW HIRING)

Freelance Backend Python information

See Phoenix, AZ salary details

$15.9K

$147.2K

$189.6K

How much do freelance backend python jobs pay per year?

As of May 29, 2026, the average yearly pay for freelance backend python in Phoenix, AZ is $147,182.00, according to ZipRecruiter salary data. Most workers in this role earn between $144,500.00 and $166,300.00 per year, depending on experience, location, and employer.

What is the difference between Freelance Backend Python vs Backend Developer?

AspectFreelance Backend PythonBackend Developer
CredentialsOften self-taught or with certifications in Python, web development, or related fieldsBachelor's degree in Computer Science or related field, with experience in backend technologies
Work EnvironmentIndependent, remote, project-basedFull-time or part-time, in-office or remote, employed by a company
Industry UsageFreelance platforms, tech startups, consultingTech companies, enterprises, startups
Search & Comparison IntentLooking for freelance opportunities, project-based workSeeking full-time or contract backend roles

Freelance Backend Python professionals typically work independently on project-based tasks, often remotely, and may not require formal degrees but should have strong Python skills. Backend Developers usually work as part of a team within a company, often holding formal education credentials. Both roles involve backend technologies, but their work settings and employment types differ significantly.

What are popular job titles related to Freelance Backend Python jobs in Phoenix, AZ? For Freelance Backend Python jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Freelance Backend Python jobs in Phoenix, AZ look for? The top searched job categories for Freelance Backend Python jobs in Phoenix, AZ are:
Infographic showing various Freelance Backend Python job openings in Phoenix, AZ as of May 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 53% Physical, 2% Hybrid, and 45% Remote job distribution, with an average salary of $147,182 per year, or $70.8 per hour.
LLM Agent Engineer (Freelance, Remote)

LLM Agent Engineer (Freelance, Remote)

Outlier AI

Phoenix, AZ • Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

About the Project

Outlier helps the world’s most innovative companies improve their AI agents by providing human feedback. Do you want to shape the future of autonomous agents like OpenClaw?

We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents. Our projects focus on teaching these systems how to design, coordinate, and optimize complex, real-world architectural workflows.

Whether you are a passionate orchestration guru or experienced software developer — we want you to help us train the world's most advanced generative systems.

Ideal Qualifications

  • 2+ years of experience in backend engineering, AI automation, or complex systems integration.
  • Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting).
  • Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases.
  • Practical experience building for live, non-mocked environments and handling multi-turn system interactions.
  • Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors.

Nice to have

  • Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output.
  • Hands-on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems.
  • High level of comfort implementing persistent state and session discovery using MEMORY.md to track agent progress.
  • Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.