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Contractual Ai Coding Trainer Jobs (NOW HIRING)

... AI model training and inference. Work closely with domain experts to ensure compliance with healthcare regulations and payer requirements. Participate in code reviews, testing, and deployment ...

About the team The Codex Deployment Engineering team helps customers adopt OpenAI's coding tools ... Have experience delivering large, high-impact workshops or technical training to engineering teams ...

About the team The Codex Deployment Engineering team helps customers adopt OpenAI's coding tools ... Have experience delivering large, high-impact workshops or technical training to engineering teams ...

About the team The Codex Deployment Engineering team helps customers adopt OpenAI's coding tools ... Have experience delivering large, high-impact workshops or technical training to engineering teams ...

... Training Support, Parental Paid Leave, and much more. Join us and make a difference in National ... Integrate AI into engineering workflows for requirements analysis, code generation, testing ...

$50/hr

Cover practical scenarios: component generation, refactoring with AI suggestions, debugging flows, test writing, code review augmentation * Conduct live, interactive training sessions and workshops;

... Training Support, Parental Paid Leave, and much more. Join us and make a difference in National ... Integrate AI into engineering workflows for requirements analysis, code generation, testing ...

... code review, QA, and documentation--to leverage AI agents and automated workflows, reducing cycle time by 30-50%. Cultural Enablement: Design and deliver workshops, training sessions, and playbooks ...

AI/ML Engineer 2 Job Summary: Responsible for the end-to-end design, development, and deployment of ... training/fine-tuning workflows. * Reviews code, mentors junior engineers, and contributes to team ...

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Contractual Ai Coding Trainer information

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How much do contractual ai coding trainer jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for contractual ai coding trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What is the difference between Contractual Ai Coding Trainer vs AI Developer?

AspectContractual Ai Coding TrainerAI Developer
CredentialsRelevant certifications in AI and coding, teaching experienceAdvanced degrees in computer science or AI, programming skills
Work EnvironmentTraining sessions, workshops, online platformsSoftware development teams, R&D labs, tech companies
Employer & Industry UsageEducational institutions, training firms, corporate trainingTech companies, startups, research organizations

While both roles involve AI and coding, a Contractual Ai Coding Trainer primarily focuses on teaching and training others in AI coding skills, often on a contractual basis. An AI Developer, however, is involved in designing, developing, and deploying AI solutions within organizations. The roles differ mainly in their focus—training versus development—and their typical work environments.

More about Contractual Ai Coding Trainer jobs
What cities are hiring for Contractual Ai Coding Trainer jobs? Cities with the most Contractual Ai Coding Trainer job openings:
What are the most commonly searched types of Ai Coding Trainer jobs? The most popular types of Ai Coding Trainer jobs are:
What states have the most Contractual Ai Coding Trainer jobs? States with the most job openings for Contractual Ai Coding Trainer jobs include:
Infographic showing various Contractual Ai Coding Trainer job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

Job description

Position: AI Engineer
Location: Remote
We are seeking a highly skilled Developer with strong expertise in Artificial Intelligence (AI) coding, particularly in Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) technologies. The ideal candidate will have critical experience in payer policies, credentialing, and payer enrollment processes. Candidates with domain experience in healthcare payer systems and AI development are preferred. The role may be split between AI-focused development and credentialing/payer enrollment expertise depending on candidate strengths.
Responsibilities:
Design, Develop, implement, and optimize AI-driven solutions leveraging LLM and RAG technologies to enhance payer policy automation and decision-making.
Collaborate with cross-functional teams to design and build scalable applications supporting payer credentialing and enrollment workflows.
Analyze payer policies and translate complex business rules into technical solutions.
Maintain and improve existing AI models and integrations related to healthcare payer systems.
Support data ingestion, processing, and retrieval mechanisms to enable efficient AI model training and inference.
Work closely with domain experts to ensure compliance with healthcare regulations and payer requirements.
Participate in code reviews, testing, and deployment activities to ensure high-quality deliverables.
Document technical designs, workflows, and best practices related to AI and credentialing systems.
Educational Qualifications:
Engineering Degree - BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.
Mandatory skills:
• Proven experience in AI coding and development, specifically with Large Language Models (LLM) and Retrieval-Augmented Generation (RAG).
• Strong understanding of healthcare payer policies, credentialing, and payer enrollment processes.
• Hands-on experience with AI/ML frameworks, natural language processing (NLP), and related technologies.
• Proficiency in programming languages such as Python, Java, or similar.
• Experience of working with healthcare data standards and compliance requirements.
• Ability to work independently and collaboratively in a fast-paced environment.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills to interact effectively with technical and non-technical stakeholders
Good-to-Have Skills:
• Prior experience in healthcare payer systems Familiarity with cloud platforms (AWS, Azure, GCP) and AI service integrations.
• Knowledge of software development lifecycle (SDLC) and Agile methodologies.
• Experience with data engineering and ETL processes related to AI model training.
• Candidates with combined skills in both AI and credentialing will be highly valued.