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Genai Engineer Jobs in Georgia (NOW HIRING)

Prompt Engineering & Optimization: Iterate on complex system prompts to guide LLM behavior for ... scorecards/GenAI tools) before returning changes to the customer. Required Qualifications ...

Prompt Engineering & Optimization: Iterate on complex system prompts to guide LLM behavior for ... scorecards/GenAI tools) before returning changes to the customer. Required Qualifications ...

Lead Forward Deployed Engineer, Palantir

Atlanta, GA ยท On-site

$98K - $129K/yr

Mentor and develop junior FDEs GenAI Solution Development * Architect and oversee delivery of LLM ... Engineering & Data Foundations * Review and contribute to production-quality code * Guide ...

... GenAI models and automation capabilities. Qualifications * 5+ years of handson experience in ... Bachelor's degree in Business, Engineering, Computer Science, Information Systems, or related field.

Lead AI/ML Engineer

Atlanta, GA ยท On-site

$98K - $129K/yr

Lead AI/ML Engineer Location: Remote Duration: Full-time Note ... Need Exceptional exp in AI/ML concepts (GenAI, Agentic, RAG), Vector DB works, news recommendation ...

Building and scaling multi-layer serving architectures for ML and GenAI/LLM models, making key ... Set engineering standards and mentor junior engineers, elevating team practices in system design ...

Showing results 41-60

Genai Engineer information

What are some typical challenges a GenAI engineer faces when deploying AI models in production environments?

GenAI Engineers often encounter challenges such as ensuring model scalability, addressing bias in generated outputs, and maintaining performance consistency in real-world applications. Deploying generative AI models requires careful monitoring to prevent unexpected or inappropriate outputs, as well as efficient resource management to handle large-scale computations. Collaborating closely with data engineers, product managers, and ML operations teams is essential to streamline deployment pipelines and quickly resolve issues that arise in live environments.

What is a GenAI engineer?

A GenAI Engineer is a professional who specializes in designing, developing, and deploying generative artificial intelligence (AI) models and applications. This role involves working with advanced machine learning techniques, such as large language models and generative adversarial networks, to create systems that can generate text, images, code, or other content. GenAI Engineers collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into products and services, ensuring ethical use and scalability. They also stay updated on the latest developments in AI research to continually improve model performance and effectiveness.

What is the difference between Genai Engineer vs Data Scientist?

AspectGenai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI/ML frameworksDegree in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentDevelops AI models, fine-tunes generative AI systems, collaborates with AI teamsAnalyzes data, builds predictive models, interprets complex datasets
Employer & Industry UsageTech companies, AI startups, research labs focusing on generative AIFinance, healthcare, marketing, and tech firms analyzing data for insights

While both roles require strong technical skills and a background in data or AI, Genai Engineers focus on developing and deploying generative AI models, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap but serve different primary functions within AI and data-driven organizations.

What are the key skills and qualifications needed to thrive as a GenAI engineer, and why are they important?

To thrive as a GenAI Engineer, you need expertise in machine learning, deep learning, and programming languages such as Python, along with a solid understanding of generative models like GANs and transformers. Familiarity with frameworks such as TensorFlow or PyTorch, and experience with cloud platforms and MLOps tools, are highly valuable; advanced degrees or certifications in AI or data science are often preferred. Strong problem-solving, creativity, and communication skills help GenAI Engineers design innovative solutions and effectively collaborate with multidisciplinary teams. These skills ensure the development of robust, scalable generative AI systems that address complex real-world challenges.
What are popular job titles related to Genai Engineer jobs in Georgia? For Genai Engineer jobs in Georgia, the most frequently searched job titles are:
What cities in Georgia are hiring for Genai Engineer jobs? Cities in Georgia with the most Genai Engineer job openings:
Infographic showing various Genai Engineer job openings in Georgia as of August 2026, with employment types broken down into 87% Full Time, 6% Part Time, 1% Temporary, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

GenAI Tuning Analyst

USAN

Norcross, GA โ€ข On-site

Full-time

Medical, Retirement, PTO

Posted 12 days ago


Job description

****Applicants must be authorized to work for ANY employer in the U.S.

We are unable to sponsor or take over sponsorship of an employment Visa at this time. 

No agencies please.


Role Overview 

As a GenAI Tuning Analyst, you will be responsible for the continuous improvement, accuracy, and "brand voice" of our Generative AI deployments within the Contact Center ecosystem, including agentic bots. You will work at the intersection of data science, linguistics, and customer operations to ensure our AI agents and agent-assist tools provide precise, empathetic, and compliant resolutions. 


This role requires a professional learner; a high-signal individual who pairs raw brainpower and adaptability with the hunger to master the evolving science of AI performance. 


Your goal is to transform generic LLM output into specialized, contact center domain-aware intelligence. 


Key Responsibilities 

  • RLHF & Quality Calibration: Lead Reinforcement Learning from Human Feedback (RLHF) cycles. You will review AI-generated outputs and "grade" them based on accuracy, empathy, and adherence to compliance protocols. 
  • Participate in Customer Tuning monthly meetings pertaining to a complete suite of USAN AI Product Specific deployments. 
  • Performance Monitoring: Define and track AI-specific KPIs, such as Hallucination RateRefusal Rate, and Intent Accuracy, alongside traditional metrics like First Contact Resolution (FCR)
  • Bias & Safety Guardrails: Implement and monitor safety filters to ensure the AI remains neutral, avoids prohibited topics, and protects PII (Personally Identifiable Information). 
  • Cross-Functional Collaboration: Partner with Subject Matter Experts (SMEs) in Legal, Compliance, and Operations to translate business policy into technical model constraints. 
  • Prompt Engineering & Optimization: Iterate on complex system prompts to guide LLM behavior for specific contact center use cases (e.g., automated summaries, live chat responses, and knowledge base retrieval). 
  • Data Curation: Identify and curate high-quality "golden datasets" from historical call transcripts and chat logs to be used for fine-tuning and few-shot prompting. 

Ideal Candidate Skills 

Analytical Pattern Recognition: Naturally identifies patterns in data and customer language, using strong data and business analytics skills to interpret trends and organize information effectively. 

Customer-facing skills for both the supervisory and executive sponsors of AI deployed in USAN’s cloud contact center offerings. 

Comfort with Ambiguity: Able to make thoughtful decisions in gray areas, applying sound judgment to determine how conversational intents should be categorized, merged, or preserved. 

Curiosity About Customer Communication: Interested in how customers naturally express their needs and are able to translate that language into meaningful insights for AI optimization. 

Process Improvement Mindset: Enjoys working with data repeatedly while finding smarter ways process and analyzing it, such as building Excel formulas, spotting systematic issues, and improving workflows. 

Trust-Based Collaboration: Builds credibility and trust with clients and internal teams while working collaboratively to improve AI performance and data quality. 

Functional Requirements Writing: Translate customer feedback into actionable product improvements by gathering input, researching root causes, writing clear technical requirements for developers, and analyzing post-update results (e.g., for agent scorecards/GenAI tools) before returning changes to the customer. 

Required Qualifications 

Experience 

  • 1-2 years in AI/NLP, Data Analysis, high-level Contact Center Operations.  
  • Analyzing Intent Accuracy to identify gaps in the AI’s natural language understanding (NLU/NLP).  
  • UAT Support: Experience assisting in User Acceptance Testing for new AI features or tool rollouts.  
  • Secondary experience in Quality Assurance is a plus.  


Technical Skills

  • Proficiency in prompt engineering techniques (Chain-of-Thought, Few-Shot, Zero Shot).
  • Basic understanding of LLM architectures (GPT-4, Claude, Llama).
  • Skilled at identifying trends in customer interaction data to suggest process improvements.  


Communication

  • Exceptional written and verbal communication skills with an obsession over tone, grammar, and brand consistency.
  • Ability to act as a bridge between technical teams and frontline operations.  
  • Moderate customer meetings to align with company direction on our AI tools.   

Preferred "Bonus" Skills 

  • Experience with RAG (Retrieval-Augmented Generation) frameworks. 
  • Background in Linguistics or Cognitive Science. 
  • Experience with data visualization tools (Tableau/PowerBI) and basic SQL to pull interaction data. 
  • Familiarity with Contact Center platforms (e.g., Amazon Connect Workspaces, Salesforce Service Cloud, Genesys, Nice, or HubSpot). 

Why This Role Matters 

In the modern contact center, the AI is the first impression. The Tuning Analyst ensures that impression is not just intelligent, but human-centric and helpful. 


Job Benefits:
•Healthcare benefits
•401K plan
•Paid company holidays
•Paid vacation
•Business casual work environment
•Annual performance based bonus program


Company Description

United States Advanced Network, In. (USAN) is a privately held corporation based out of Norcross, GA (a suburb of Atlanta, GA).  USAN is an AWS Advanced Tier Partner specializing in Amazon Connect, helping organizations design and deploy scalable, AI-driven customer interactions that accelerate time to value and maximize ROI. With over 35 years of deep contact center expertise, USAN delivers modern agentic CX solutions and a white-glove approach to optimizing and managing cloud contact center environments through its managed services.   

For more information, please visit us at www.usan.com