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Part Time Ai Agent Developer Jobs in New York (NOW HIRING)

... or part-time. We're mission-driven and obsessed with our customers, and we believe humans and AI ... Partner with data science, engineering, and analytics to shape models, signals, and data products.

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Part Time Ai Agent Developer information

What does a part time AI agent developer do?

A Part Time AI Agent Developer designs, builds, and maintains artificial intelligence (AI) agents or software that can perform tasks autonomously or assist users, often using machine learning and natural language processing. Working part-time, they may contribute to specific projects, troubleshoot code, optimize models, or integrate AI agents into larger systems. This role often requires programming skills, familiarity with AI frameworks, and the ability to collaborate with other developers or stakeholders.

What are the key skills and qualifications needed to thrive as a part time AI agent developer?

To thrive as a Part Time AI Agent Developer, you need a solid background in computer science, machine learning, and programming languages such as Python, often supported by relevant coursework or experience. Familiarity with AI frameworks like TensorFlow or PyTorch, version control systems like Git, and cloud platforms such as AWS or Azure is typically required. Strong problem-solving skills, effective time management, and clear communication are essential soft skills in this role. These qualifications enable developers to efficiently build high-quality AI agents while balancing part-time work schedules and collaborating with teams.

How does working as a part time AI agent developer impact opportunities for skill development and career progression?

As a part-time AI Agent Developer, you'll often have the flexibility to work on a variety of projects, which can accelerate your exposure to different AI technologies and frameworks. Although part-time roles may not always provide the same structured advancement paths as full-time positions, they frequently offer opportunities to collaborate with cross-functional teams, attend training sessions, and contribute to innovative solutions. This hands-on experience can help you build a strong portfolio and make valuable industry connections, both of which are instrumental for future career growth in AI development.

What are the most commonly searched types of Ai Agent Developer jobs in New York?

The most popular types of Ai Agent Developer jobs in New York are:

What are popular job titles related to Part Time Ai Agent Developer jobs in New York?

For Part Time Ai Agent Developer jobs in New York, the most frequently searched job titles are:

What job categories do people searching Part Time Ai Agent Developer jobs in New York look for?

The top searched job categories for Part Time Ai Agent Developer jobs in New York are:

What cities in New York are hiring for Part Time Ai Agent Developer jobs?

Cities in New York with the most Part Time Ai Agent Developer job openings:

Infographic showing various Part Time Ai Agent Developer job openings in New York as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Software Engineering Evaluation Specialist

Mindrift

Brooklyn, NY โ€ข On-site

$35/hr

Part-time

Posted 17 days ago


Key responsibilities

  • Design coding tasks that include a broken piece of software within a Docker environment, with instructions, tests, and reference solutions.

  • Build reproducible Docker environments with pinned dependencies and write verification tests that are deterministic and non-flaky.

  • Create instruction documents resembling Jira tickets and reference scripts demonstrating task solvability.


Job description

Please submit your CV in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

About the Role

You'll design coding tasks that challenge frontier AI coding agents. Each task is a self-contained Docker environment with a broken piece of software; an AI agent attempts the fix; automated tests verify the outcome. Your deliverable is the full task package: broken code, tests, instructions, and a reference solution proving the task is solvable.

Responsibilities:

  • Invent a realistic developer scenario - a real bug, a broken ETL, a missing feature - not a toy problem.
  • Build a reproducible Docker environment with pinned dependencies.
  • Write a pytest that verifies outcomes, not specific commands - deterministic, non-flaky, and does not leak the fix.
  • Write an instruction.md that reads like a Jira ticket a developer would receive.
  • Write a reference solve.sh proving the task is solvable.
  • Calibrate difficulty so current state-of-the-art agents solve the task 20-60% of the time.
  • Iterate based on feedback from expert QA reviewers.
  • Later: review other authors' tasks as a QA reviewer.

Not in scope

  • Data labeling, prompt engineering.
  • Production code to ship - you design problems and verification for AI agents.
  • Leetcode puzzles - scenarios must look like real developer work.
  • Not every candidate task ships - quality over quantity.

Requirements

  • 3+ years of production software development in one backend stack - Python, Go, Node.js, Java, or Rust. Depth in one stack beats breadth.
  • Python + pytest fluency - required regardless of primary stack. The task harness is pytest-based even when the broken app is in another language. Fixtures, parametrize, monkeypatch, timeouts, conftest.py.
  • Docker authoring - reproducible Dockerfiles, pinned dependencies, multi-stage builds when needed, non-root user.
  • Linux & Bash - comfort debugging inside containers (strace, lsof, journalctl); shell beyond set -euo pipefail.
  • AI coding agent experience - Claude Code, Cursor, Roo Code, or similar, on non-trivial work. You can cite a specific time the AI was confidently wrong and how you caught it.
  • English - B2+ written.

Not a fit

  • Data Science, ML, or Computer Vision engineers without backend-engineering output.
  • Manual QA testers without automation or test authoring.
  • Frontend-only, low-code / no-code, IT Support, or Business Analysts.
  • Engineers who have never written pytest from scratch.
  • Junior, intern, or assistant as the most recent role.

Preferred qualifications

  • Domain depth in Security, System Administration (nginx / systemd / cron), Scientific Computing (NumPy / PyTorch / SciPy), DevOps, or Git internals.
  • Modern Python tooling (uv, poetry, pyproject.toml).
  • Coverage tooling (pytest-cov, coverage.py, gcov, llvm-cov, kcov).
  • Fuzzing or property-based testing (Hypothesis).
  • Prior contribution to agent-evaluation benchmarks or related frameworks.

Process

Apply Pass qualification (90-minute sample-task screen + short behavioral interview) Join a project Complete tasks Get paid.

Time commitment

  • Onboarding: ~10 hours per first task.
  • Steady state: ~5 hours per task, 2-4 parallel tasks per author.
  • Realistic weekly load: 8-20 hours. Higher volume available for top performers.
  • You choose when and how to contribute; tasks must be submitted by the deadline and meet acceptance criteria.

Compensation:

  • Paid contributions, rates up to $35/hour*.
  • Task-based compensation equivalent to hourly rate, depending on performance and volume.
  • Some projects include incentive payments.

*Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be provided to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

Apply

Submit your CV via the Mindrift platform. Indicate your English level, note this role (Software Engineering Evaluation Specialist - Terminal Bench), and include a GitHub profile link if available.