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Ai Accelerator Jobs in Georgia (NOW HIRING)

Coram AI co

Account Executive

Atlanta, GA · On-site

$130 - $200/hr

At Coram AI, we're reimagining video security for the modern world. Our cloud-native platform uses ... In return, you are able to earn uncapped commission, reach accelerators, and sell into a rapidly ...

BECPOS

Principal AI Engineer

Atlanta, GA · Remote

Develop reusable enterprise AI patterns, frameworks, and accelerators. * Establish AI best practices, governance standards, and engineering guidelines. * Lead architecture and deployment of AI ...

Digital Insight

Principal AI Engineer

Atlanta, GA · Remote

Develop reusable enterprise AI patterns, frameworks, and accelerators. * Establish AI best practices, governance standards, and engineering guidelines. * Lead architecture and deployment of AI ...

NCR

Principal AI Engineer

Atlanta, GA · Remote

Develop reusable enterprise AI patterns, frameworks, and accelerators. * Establish AI best practices, governance standards, and engineering guidelines. * Lead architecture and deployment of AI ...

NCR Corporation

Principal AI Engineer

Atlanta, GA · On-site

Develop reusable enterprise AI patterns, frameworks, and accelerators. * Establish AI best practices, governance standards, and engineering guidelines. * Lead architecture and deployment of AI ...

NCR Corporation

Principal AI Engineer

Atlanta, GA · On-site

$180 - $260/hr

Develop reusable enterprise AI patterns, frameworks, and accelerators.Establish AI best practices, governance standards, and engineering guidelines.Lead architecture and deployment of AI-powered ...

Accenture

Sr AI Architect

Atlanta, GA

Develop and contribute to AI assets, accelerators, and methodologies to enhance organizational capability and delivery efficiency. Collaborate across global teams and partner ecosystems to share ...

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Ai Accelerator information

What is an AI accelerator?

AI Accelerators are specialized hardware or software systems designed to optimize and speed up artificial intelligence (AI) and machine learning (ML) workloads. They process complex computations required by AI algorithms more efficiently than general-purpose CPUs, enabling faster training and inference for deep learning models. Common examples of AI accelerators include GPUs, TPUs, FPGAs, and dedicated AI chips. These technologies are widely used in data centers, edge devices, and consumer electronics to support applications like image recognition, natural language processing, and autonomous vehicles.

What are the key skills and qualifications needed to thrive as an AI accelerator, and why are they important?

To thrive as an AI Accelerator, you need a deep understanding of machine learning algorithms, computer architecture, and parallel computing, often supported by a degree in computer science, electrical engineering, or a related field. Familiarity with hardware description languages (HDLs), CUDA, TensorFlow, and specific AI accelerator platforms is typically required. Strong problem-solving abilities, collaboration, and adaptability are essential soft skills for navigating complex projects and interdisciplinary teams. These skills and qualities are crucial for designing, optimizing, and deploying high-performance AI systems that meet real-world demands.

How does an AI accelerator typically collaborate with data scientists and engineering teams on AI projects?

AI Accelerators work closely with both data scientists and engineering teams to bridge the gap between model development and deployment. They often help optimize AI models for efficiency and scalability, ensuring they run effectively on various hardware platforms. Regular collaboration includes reviewing model architectures, suggesting improvements for speed and accuracy, and troubleshooting performance bottlenecks together. This cross-functional teamwork is essential for translating research breakthroughs into robust, real-world AI solutions.

What does an AI accelerator do?

An AI accelerator is a professional who develops and optimizes hardware and software solutions to improve the performance of artificial intelligence models. They often work with specialized hardware like GPUs or TPUs and use programming skills in frameworks such as TensorFlow or PyTorch to enhance AI processing speed and efficiency.

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For Ai Accelerator jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Ai Accelerator jobs in Georgia look for?

The top searched job categories for Ai Accelerator jobs in Georgia are:

What cities in Georgia are hiring for Ai Accelerator jobs?

Cities in Georgia with the most Ai Accelerator job openings:

Ai Accelerator jobs near you
Infographic showing various Ai Accelerator job openings in Georgia as of August 2026, with employment types broken down into 71% Full Time, 19% Part Time, 7% Contract, and 3% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Forward Deployed Engineer Agentic AI - On site/hybrid

Talent Search PRO

Atlanta, GA • On-site

$200K - $250K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 25 days ago

Key responsibilities

  • Partner with enterprise stakeholders to identify AI opportunities and define measurable business outcomes

  • Build rapid proof-of-value and MVP AI solutions using modern GenAI and agentic frameworks

  • Design scalable AI architectures including orchestration, governance, observability, and security controls

Job description

Forward Deployed Engineer – Agentic AI


Salary: $200,000 – $250,000 + Bonus

Why This Role?
  • Work on enterprise-scale GenAI and Agentic AI initiatives
  • Exposure to Fortune 2000 AI transformation programs
  • High visibility with executive stakeholders and enterprise clients
  • Strong compensation package with bonus eligibility
  • Medical, dental, vision, 401(k) match, paid parental leave, PTO, and disability coverage
About the Role

Seeking a Forward Deployed Engineer to help enterprise clients design, prototype, and scale GenAI and Agentic AI solutions. This role sits at the intersection of engineering, solution architecture, and executive-facing consulting.

You will work directly with senior business leaders and technical teams to rapidly build proof-of-value solutions, architect scalable AI systems, and accelerate enterprise AI adoption across complex environments.

This is a highly hands-on role focused on shipping real AI systems, not presentations.

Responsibilities
  • Partner with enterprise stakeholders to identify AI opportunities and define measurable business outcomes
  • Build rapid proof-of-value and MVP AI solutions using modern GenAI and agentic frameworks
  • Design scalable AI architectures including orchestration, governance, observability, and security controls
  • Develop AI workflows with tool integrations, enterprise data connectivity, and lightweight user experiences
  • Implement RAG architectures, vector search, retrieval strategies, and evaluation frameworks
  • Integrate AI solutions with enterprise platforms including AWS, Azure, GCP, Salesforce, SAP, ServiceNow, and Microsoft ecosystems
  • Support technical discovery sessions, workshops, demos, and executive presentations
  • Create reusable AI accelerators, templates, evaluation suites, and reference architectures
  • Collaborate with engineering, cloud, product, and delivery teams to transition solutions into production environments
Requirements
  • 8+ years of experience in software engineering, AI engineering, solution architecture, or technical consulting
  • Strong experience building enterprise GenAI or Agentic AI solutions
  • Experience with LLM orchestration, tool-calling, planning workflows, and human-in-the-loop systems
  • Hands-on experience with RAG pipelines, vector databases, embeddings, and retrieval evaluation
  • Strong full-stack engineering fundamentals including APIs, integrations, distributed systems, and cloud-native architectures
  • Proficiency in Python and at least one additional language such as TypeScript, Java, or Go
  • Experience with AWS, Azure, or GCP environments
  • Familiarity with CI/CD, containers, observability, and AI governance concepts
  • Strong communication skills with the ability to engage executive stakeholders
  • Bachelor’s degree required
Preferred Background
  • Experience deploying production-grade GenAI systems
  • Consulting or client-facing engineering experience preferred
  • Exposure to AI governance, AgentOps, telemetry, and compliance frameworks
  • Experience within enterprise AI consulting or hyperscaler ecosystems is highly valued
  • Background supporting industries such as financial services, retail, manufacturing, hospitality, or healthcare is a plus
Additional Details
  • Full-time opportunity
  • Bonus eligible
  • Occasional travel required for workshops and client engagements
  • Sponsorship not available
  • Candidates should have fewer than 10 years of total experience preferred by the hiring team