> Markdown version of [/jobs/ext/2103326-ai-llm-engineer](https://www.wearedevelopers.com/jobs/ext/2103326-ai-llm-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI LLM Engineer - **Company:** TalentOla View all jobs - **Location:** Alpharetta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Performance Tuning, Software Deployment, Software Engineering, Enterprise Software Applications, Chatbots, Large Language Models, Prompt Engineering, IT Architecture, Low Latency - **Published:** August 18, 2026 - **Apply:** https://www.careerjet.com/jobad/usead0cb8d54ea157aa0ca1379d76a9bd3 ## About the Role Software Engineering: 5+ years of professional software development experience. LLM Expertise: 3+ years of hands-on experience working directly with Large Language Models. Prompt & Conversation Design: 3+ years of experience designing prompt strategies and managing conversation frameworks. Response Tuning: 3+ years of experience implementing, tuning, and auditing conversational AI outputs. o Providing traceable response generation. o Developing reusable explanation templates for pricing methods, revenue sharing models, and expense calculations. o Conducting prompt tuning and model optimization. o Implement hallucination mitigation controls. Technical Skills Proven track record of deploying production-ready AI solutions at scale. Deep understanding of API integration, tool-calling (function calling), and agentic workflows. Experience embedding regulatory compliance, financial traceability, or audit trails into AI responses. ## Description We are seeking a Senior AI LLM Engineer to design, deploy, and optimize production-grade conversational AI systems. You will build scalable tool-calling frameworks, integrate AI models with enterprise applications, and implement strict hallucination mitigation controls. A key focus of this role is developing traceable response systems and reusable explanation templates for complex financial calculations. Key Responsibilities AI Architecture & Production Deployment Deploy Solutions: Build and maintain scalable, production-grade LLM applications. Integrate Systems: Connect AI models with enterprise applications and secure APIs. Build Frameworks: Develop robust tool-calling frameworks to orchestrate model-API interactions. Prompt Engineering & Conversation Design Design Strategies: Create advanced prompt strategies and conversation management frameworks. Tune Responses: Optimize conversational context to ensure highly accurate user experiences. Mitigate Risks: Implement automated controls to detect and eliminate model hallucinations. Financial Logic & Traceability Ensure Traceability: Build mechanisms that provide auditable, step-by-step reasoning for generated outputs. Develop Templates: Create reusable explanation templates for pricing methods, revenue sharing models, and expense calculations. Optimize Performance: Conduct continuous prompt tuning and model optimization for cost, latency, and accuracy. ## Related Videos - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Architectures that we can use with .NET](https://www.wearedevelopers.com/videos/935-architectures-that-we-can-use-with-net) - [Using LLMs in your Product](https://www.wearedevelopers.com/videos/1186-using-llms-in-your-product) - [Testing AI Agents: Automated Evaluation for Chatbots & RAG Systems](https://www.wearedevelopers.com/videos/100300-testing-ai-agents-automated-evaluation-for-chatbots-rag-systems) - [Three years of putting LLMs into Software - Lessons learned](https://www.wearedevelopers.com/videos/1508-three-years-of-putting-llms-into-software-lessons-learned) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [The Prompt Engineer ✍️](https://www.wearedevelopers.com/magazine/216-the-prompt-engineer) - [Who Owns Your Content in the Age of LLMs?](https://www.wearedevelopers.com/magazine/610-who-owns-your-content-in-the-age-of-llms) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)