AI Engineer - Gen AI - Trainer - Part-Time - Remote

GIST Management Solutions; United States; Remote; USD 83,000 - 165,000; Part time

Benefits offered by this job

Flexible schedule

Remote work

Job summary

GIST Management Solutions is seeking a part-time Generative AI Engineer Trainer to deliver live online instruction to USA-based students and professionals. You will teach LLM fundamentals, RAG, and agentic AI, guiding learners through hands-on labs and capstone projects using Python, LangChain, and cloud-based AI services.

The role emphasizes real-world labs, secure coding practices, and engaging virtual sessions aligned with US time zones.

Qualifications

• 4+ years of professional software engineering experience with 2+ years building production LLM-based systems.
• Strong proficiency in Python for backend development and AI engineering.
• Hands-on experience building LLM applications using LangChain, LangGraph or equivalent frameworks.
• Experience with RAG, embeddings, vector databases, semantic search, and retrieval pipelines.
• Practical experience building Agentic AI systems with tool calling, memory, state management, and multi-step workflows.
• Familiarity with MCP, prompt engineering, context engineering, and AI security risks.
• Experience with LLM evaluation, testing, observability, and tracing (LangSmith or similar).
• Strong understanding of LLMs, NLP, transformers, and Generative AI architectures.
• Experience with OpenAI, Anthropic, Bedrock, Azure OpenAI, Llama or comparable platforms.
• Cloud experience, preferably Microsoft Azure, and cloud-native AI architectures.
• Excellent spoken English and ability to present complex topics to a US audience.

Responsibilities

• Deliver live, interactive online Generative AI training to USA-based learners aligned with US time zones.
• Teach LLM fundamentals, Generative AI, Transformers, embeddings, NLP, foundation models, and modern AI architectures.
• Train learners to build LLM applications using Python, LangChain, LangGraph, and related frameworks.
• Teach RAG concepts including document processing, embeddings, vector databases, semantic search, and context optimization.
• Instruct on Agentic AI topics: agents, tool calling, memory, state management, and orchestration.
• Cover MCP, function/tool calling, and integration of AI agents with external APIs.
• Discuss prompt engineering, context engineering, outputs, injection risks, and AI security best practices.
• Guide learners in LLM evaluation and observability using datasets and LangSmith.
• Provide capstone project mentorship from architecture to deployment and conduct mock interviews.

Skills

Python programming

LLM development

RAG systems

Agentic AI

Prompt engineering

Context engineering

LLM evaluation

LangSmith

Public speaking

English communication

Tools

LangChain

LangGraph

OpenAI platform

Azure OpenAI

Amazon Bedrock

Anthropic Claude

Llama

REST APIs

FastAPI

Cloud deployment

Job description

Job Title: Generative AI Engineer Trainer Part-Time | Remote

Job Type: Part-Time / Freelance

Work Mode: Remote / Online

Role: Generative AI Engineer Trainer (LLMs, RAG, Agentic AI & AI Engineering)

Training Audience: Students and working professionals in the USA

Job Description

We are looking for an experienced Generative AI Engineer Trainer to deliver live, instructor‑led online training to students and working professionals based in the USA.

Important: This is a Generative AI Engineer Trainer role and NOT a full‑time software engineering role. The ideal candidate must have strong hands‑on experience building production‑grade LLM applications, RAG systems, AI agents, tool‑using workflows, and cloud‑based AI solutions, along with a passion for mentoring learners through practical labs and real‑world projects.

Key Responsibilities

• Deliver live, interactive online Generative AI training to USA‑based learners aligned with US time zones.
• Teach LLM fundamentals, Generative AI, Transformers, embeddings, NLP, foundation models, and modern AI application architectures.
• Train learners to build LLM applications using Python, LangChain, LangGraph, and equivalent AI frameworks.
• Teach Retrieval‑Augmented Generation (RAG), including document processing, chunking, embeddings, vector databases, semantic search, retrieval, reranking, and context optimization.
• Train learners on Agentic AI, including AI agents, tool calling, memory, state management, multi‑step workflows, and agent orchestration.
• Teach Model Context Protocol (MCP), function/tool calling, and integration of AI agents with external systems and APIs.
• Cover prompt engineering, context engineering, structured outputs, prompt injection risks, AI security, and responsible AI practices.
• Guide learners through LLM evaluation and observability using test datasets, automated evaluations, LLM‑as‑a‑judge approaches, tracing, and tools such as LangSmith.
• Train learners on foundation models and platforms including OpenAI, Anthropic Claude, Amazon Bedrock, Azure OpenAI, Llama, or comparable services.
• Teach AI backend development using Python, FastAPI, Pydantic, REST APIs, and modern software engineering practices.
• Guide learners through cloud‑based AI application deployment, preferably using Microsoft Azure and related AI services.
• Mentor students through an end‑to‑end, portfolio‑ready Generative AI / Agentic AI capstone project, including architecture reviews, debugging, code reviews, and deployment.
• Conduct mock technical interviews and provide constructive feedback to prepare candidates for Generative AI Engineer and AI Engineer roles.

Required Skills & Experience

• Minimum 4+ years of professional software engineering experience, including 2+ years of hands‑on experience building LLM‑based systems in production.
• Strong proficiency in Python for backend development, AI engineering, and machine learning.
• Hands‑on experience building LLM applications using LangChain, LangGraph, or equivalent frameworks.
• Strong experience with RAG, embeddings, vector databases, semantic search, and retrieval pipelines.
• Practical experience building Agentic AI systems, including tool calling, memory, state management, and multi‑step workflows.
• Experience with MCP, prompt engineering, context engineering, and understanding of prompt injection and AI security risks.
• Experience with LLM evaluation, testing, observability, and tracing using LangSmith or equivalent tools.
• Strong understanding of LLMs, NLP, Transformers, deep learning, and Generative AI architectures.
• Experience with foundation models and services such as OpenAI, Anthropic, Amazon Bedrock, Azure OpenAI, Llama, or comparable platforms.
• Hands‑on cloud experience, preferably with Microsoft Azure and cloud‑native AI architectures.
• Exceptional spoken English and presentation skills, with comfort teaching technical topics interactively to a US audience.
• Previous experience in technical instruction, bootcamp coaching, mentoring, corporate training, or leading engineering teams is highly preferred.
• Must be willing and available to deliver sessions during US‑friendly hours (EST morning or evening windows).

Preferred Certifications

Microsoft Certified: Azure AI Engineer Associate

AWS Certified Machine Learning / Machine Learning Engineer

AWS Certified Solutions Architect

Comparable industry‑recognized AI, cloud, machine learning, or software engineering certifications.

Important Note

This is a part‑time, remote trainer opportunity only. Candidates looking exclusively for a full‑time AI Engineer / Software Engineer position should not apply.

Candidates should apply only if they have 4+ years of professional software engineering experience, hands‑on production LLM experience, strong GenAI/Agentic AI capabilities, and the availability to train students and professionals in the USA.