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Commission Ai Agent Developer Jobs in Portland, ME

eNett

Senior AI Product Manager (AI Builder)

Portland, ME · On-site

$129K - $170K/yr

Hands-on experience with agent frameworks, prompt/context engineering tools, or AI experimentation ... Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales ...

New

WEX

Senior AI Product Manager (AI Builder)

Portland, ME · On-site

$129K - $170K/yr

Hands-on experience with agent frameworks, prompt/context engineering tools, or AI experimentation ... Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales ...

New

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All JobsAi Agent Developer JobsCommission Ai Agent Developer JobsCommission Ai Agent Developer Jobs in Portland, ME

Commission Ai Agent Developer information

What is a Commission AI Agent Developer?

Commission AI Agent Developers are professionals who design, build, and deploy artificial intelligence (AI) agents that operate on a commission-based model. These developers create AI systems—such as chatbots, sales agents, or customer service bots—that help automate tasks and drive results, often earning a commission or fee based on the performance or outcomes generated by their agents. They typically possess skills in AI programming, machine learning, and automation, and work with clients to tailor solutions that meet specific business goals. The demand for Commission AI Agent Developers is growing as more businesses adopt AI-driven technologies to enhance productivity and sales. Their work often involves continuous optimization and monitoring to ensure the AI agents remain effective and profitable.

How does a Commission AI Agent Developer typically collaborate with sales and marketing teams to optimize agent performance?

As a Commission AI Agent Developer, you will frequently work alongside sales and marketing teams to tailor AI agents that effectively engage prospects and customers. This collaboration involves gathering feedback on agent interactions, analyzing performance metrics, and iterating on conversational scripts or algorithms to drive conversions. Regular meetings and data sharing ensure that the AI agents align with evolving business goals and customer preferences, making cross-functional communication a key aspect of the role. This dynamic environment allows you to see the direct impact of your work on sales outcomes while also fostering your own technical and business skills.

What are the key skills and qualifications needed to thrive as a Commission AI Agent Developer, and why are they important?

To thrive as a Commission AI Agent Developer, you need strong programming skills (often in Python), experience with machine learning frameworks, and a solid understanding of AI concepts, typically backed by a relevant degree or equivalent experience. Familiarity with AI development tools such as TensorFlow, PyTorch, and cloud platforms like AWS or Azure is commonly required. Exceptional problem-solving abilities, adaptability, and clear communication set candidates apart in this role. These skills are crucial for building effective AI agents that meet client needs and drive successful commission-based projects.

What is the difference between Commission Ai Agent Developer vs Chatbot Developer?

AspectCommission Ai Agent DeveloperChatbot Developer
Required CredentialsBachelor's in Computer Science, AI certificationsBachelor's in Computer Science, AI or software development certifications
Work EnvironmentAI development teams, financial or sales industriesCustomer service, tech companies, various industries
Employer & Industry UsageFinancial services, sales automationCustomer support, marketing, e-commerce
Comparison Search IntentUnderstanding AI-driven commission systemsBuilding conversational agents for customer interaction

The main difference is that Commission Ai Agent Developers focus on creating AI systems that automate commission calculations and sales processes, often within financial or sales industries. Chatbot Developers design conversational agents for customer support or engagement across various sectors. While both roles involve AI and programming skills, their applications and industry focus differ significantly.

What are the most commonly searched types of Ai Agent Developer jobs in Portland, ME?

The most popular types of Ai Agent Developer jobs in Portland, ME are:

What are popular job titles related to Commission Ai Agent Developer jobs in Portland, ME?

For Commission Ai Agent Developer jobs in Portland, ME, the most frequently searched job titles are:

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The top searched job categories for Commission Ai Agent Developer jobs in Portland, ME are:

Commission Ai Agent Developer jobs near you

AI Agent Trajectory Annotator and Reviewer

Bespoke Labs

Biddeford, ME • 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.

Apply