AI LLM Engineer

TalentOla; Alpharetta (GA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

TalentOla in the United States is seeking a Senior AI LLM Engineer to design, deploy, and optimize production-grade conversational AI systems, with emphasis on tool-calling frameworks, enterprise API integration, and traceable reasoning for complex calculations.

You will build reusable templates for explanations, focus on hallucination mitigation, and drive cost, latency, and accuracy improvements through continuous prompt tuning.

Qualifications

• 5+ years of professional software development experience (senior level).
• 3+ years of hands-on experience with Large Language Models.
• 3+ years designing prompt strategies and managing conversation frameworks.
• 3+ years tuning, auditing AI outputs, and implementing hallucination mitigation controls.
• Providing traceable response generation and reusable explanation templates for pricing & revenue methods.

Responsibilities

• Design, deploy, and optimize production-grade conversational AI systems.
• Build scalable tool-calling frameworks to orchestrate model-API interactions.
• Develop prompt strategies and manage conversation designs for accurate user experiences.

Skills

Software Engineering

LLM Expertise

Prompt & Conversation Design

Response Tuning

Tool-calling / function calling

API integration

Regulatory compliance / audit trails

Tools

Tool-calling frameworks

Production-grade deployment

API integration

Job description

4-Senior AI LLM Engineer

Alpharetta, GA/Coral Springs, FL/ Berkeley Heights, NJ/Omaha NE/Wilmington DE

Contract

Mphasis W2

Job Description

Skill Role Grade Location

Conversational AI Architect Level 6 or 7 Alpharetta, NJ

Job Description: Senior AI LLM Engineer

Position Overview

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.

Qualifications

Required Experience

• 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.