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Senior Ai Developer Jobs in Georgia (NOW HIRING)

Florence Healthcare - US

Senior AI Engineer

Atlanta, GA

$100K - $138K/yr

We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features. This role focuses on owning end-to-end implementation of AI systems within a product area - from ...

Aimpoint Digital

Senior AI Engineer 2026 - US

Atlanta, GA · On-site +1

$100K - $138K/yr

About the Role As a Senior AI Engineer, you will work directly with clients to design, build, deploy, and scale enterprise AI solutions. You will combine strong software engineering fundamentals with ...

Aimpoint Digital

Senior AI Engineer 2026 - US

Atlanta, GA · On-site +1

$100K - $138K/yr

About the Role As a Senior AI Engineer, you will work directly with clients to design, build, deploy, and scale enterprise AI solutions. You will combine strong software engineering fundamentals with ...

Florence Healthcare - US

Senior AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features. This role focuses on owning end-to-end implementation of AI systems within a product area - from ...

Home Depot

Senior AI Engineer (Remote)

Atlanta, GA · On-site +1

$99K - $136K/yr

The Senior AI Engineer is responsible for designing, building, scaling, and optimizing production ... Works with Product Team to ensure user stories that are developer-ready, easy to understand, and ...

Sumeru

Senior AI/ML Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior AI/ML Engineer Location: Bellevue/Seattle, WA ; Atlanta, GA, and Frisco, TX Need Local Candidates Job Overview We are seeking an AI/ML Engineer to build the intelligent systems that power ...

Kion Group AG

Senior AI Data Engineer

Atlanta, GA · On-site

$121K - $151K/yr

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and ...

Kiongroup

Senior AI Data Engineer

Atlanta, GA · On-site

$121K - $151K/yr

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and ...

Kiongroup

Senior AI Data Engineer

Atlanta, GA · On-site

$121K - $151K/yr

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and ...

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Senior Ai Developer information

What is a senior AI developer?

Senior AI Developers are experienced professionals who design, build, and implement artificial intelligence systems and solutions. They typically lead AI projects, mentor junior team members, and work on complex problems involving machine learning, deep learning, and data analysis. Their responsibilities also include collaborating with stakeholders, optimizing models for performance, and ensuring AI solutions align with business goals. Senior AI Developers usually have advanced knowledge of programming languages, frameworks, and best practices in AI development.

What are the key skills and qualifications needed to thrive as a senior AI developer?

To thrive as a Senior AI Developer, you need advanced skills in machine learning, deep learning, programming (Python, R, or Java), and a strong background in computer science or related fields, often supported by a bachelor's or master's degree. Expertise in frameworks like TensorFlow, PyTorch, scikit-learn, and experience with cloud platforms (AWS, Azure, or GCP) and relevant certifications are highly valued. Strong problem-solving, leadership, and effective communication skills help in collaborating across teams and translating complex technical concepts into business solutions. These capabilities are crucial for designing robust AI systems, driving innovation, and ensuring successful deployment in real-world applications.

What are some common challenges faced by senior AI developers when deploying models into production environments?

Senior AI Developers often encounter challenges such as ensuring model scalability and reliability, handling data drift, and integrating models with existing production systems. Balancing model performance with computational efficiency is crucial, as is maintaining compliance with data privacy regulations. Close collaboration with DevOps, data engineering, and product teams is essential to address these challenges and deliver robust, maintainable AI solutions.

What is the difference between Senior Ai Developer vs Machine Learning Engineer?

AspectSenior Ai DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models, algorithms, and applications; collaborates with data scientists and engineersDesigns, builds, and deploys machine learning models; often works in data-heavy environments
Employer & Industry UsageTech companies, research labs, AI-focused firmsTech companies, startups, data-driven industries

While both roles involve working with AI and machine learning, Senior Ai Developers focus more on creating and optimizing AI systems, whereas Machine Learning Engineers specialize in building scalable ML models and pipelines. The roles often overlap, but the Senior Ai Developer emphasizes AI application development, and the Machine Learning Engineer emphasizes deployment and data handling.

Which senior AI developer job is high paying?

Senior AI developer roles tend to be high paying in industries such as technology, finance, and healthcare, especially for those with expertise in machine learning, deep learning, and experience with tools like TensorFlow or PyTorch. Salaries can vary based on location, company size, and individual skills, but senior positions often offer six-figure compensation packages.

What are the most commonly searched types of Ai Developer jobs in Georgia?

The most popular types of Ai Developer jobs in Georgia are:

What are popular job titles related to Senior Ai Developer jobs in Georgia?

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

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

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

What cities in Georgia are hiring for Senior Ai Developer jobs?

Cities in Georgia with the most Senior Ai Developer job openings:

Senior Ai Developer jobs near you
Infographic showing various Senior Ai Developer job openings in Georgia as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Senior AI Engineer

Florence Healthcare - US

Atlanta, GA

$100K - $138K/yr

Full-time

Re-posted 22 hours ago

Job description

What You'll Bring to The Team:

We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features. This role focuses on owning end-to-end implementation of AI systems within a product area - from prototyping to production - with a strong emphasis on reliability, iteration, and measurable impact. You will work closely with product and engineering teams to turn ambiguous problems into effective AI solutions, while contributing to best practices and raising the bar for AI development.

You Will:End-to-End AI Feature Ownership
  • Design and implement AI-powered features (LLM workflows, copilots, and agent-based systems with tool use and multi-step reasoning)
  • Own the full lifecycle: prototyping evaluation production deployment iteration
  • Ensure solutions are reliable, performant, and aligned with product needs
AI System Implementation
  • Build and optimize:
    • Prompt pipelines for specific use cases
    • Retrieval systems (embeddings, chunking, ranking)
    • RAG-based workflows where needed
  • Iterate on outputs to improve quality, accuracy, and consistency
  • Design scalable and cost-efficient AI architectures for production workloads
  • Select and evaluate models (hosted vs open-source) based on use case constraints
  • Agent-Based Systems (AgentCore)
    • Design and build agentic workflows capable of multi-step reasoning and decision-making
    • Integrate agents with tools, APIs, and internal systems to perform real-world actions
    • Implement planning, execution, and reflection loops for complex tasks
    • Manage context, memory, and state across multi-step interactions
    • Balance deterministic workflows vs. agent autonomy for reliability and control
Experimentation & Evaluation
  • Run structured experiments to compare approaches (prompting, retrieval, models)
  • Define and track key metrics for AI performance (quality, latency, cost)
  • Debug and improve non-deterministic system behavior
  • Build and maintain evaluation datasets and benchmarks
  • Implement automated evaluation pipelines for continuous improvement
Collaboration & Contribution
  • Drive technical direction and influence AI adoption across teams
  • Partner with product managers and designers to scope AI features
  • Contribute to shared patterns and reusable components
  • Participate in code reviews and design discussions
  • Support and mentor mid-level engineers where needed
AI Reliability, Safety & Governance
  • Design guardrails to ensure safe and reliable AI behavior
  • Mitigate hallucinations, prompt injection, and model misuse
  • Ensure compliance with data privacy and enterprise requirements
  • Implement monitoring and observability for AI systems in production
  • Implement guardrails for agent actions (tool access control, execution boundaries)
  • Prevent failure cascades in multi-step agent workflows

An Ideal Candidate Has: 

Core AI Skills
  • Strong understanding of LLM capabilities and limitations
  • Experience with prompt engineering and structured output design
  • Hands-on experience with embeddings and vector search
  • Familiarity with RAG architectures and when to apply them
  • Experience designing agent-based architectures (AgentCore concepts)
  • Understanding of tool use, planning strategies, and memory mechanisms in LLM systems
Engineering Skills
  • 4+ years of related work experience 
  • Solid backend/system design fundamentals
  • Evaluate agent performance across multi-step tasks (task success rate, error propagation)
  • Debug and optimize agent decision-making and tool selection behavior
  • Experience building and deploying production-grade systems
  • Ability to debug complex issues, including probabilistic outputs
  • Comfort working with APIs, pipelines, and data flows
Product Thinking
  • Ability to translate user needs into effective AI solutions
  • Strong intuition for balancing quality, latency, and cost
  • Focus on delivering measurable product impact
Collaboration
  • Communicates clearly across engineering and product teams
  • Contributes to team knowledge and shared practices
What Success Looks Like:
  • Ships high-quality AI features that deliver clear user value
  • Demonstrates strong ownership from idea to production
  • Improves systems through structured iteration and experimentation
  • Contributes to team-level best practices and reusable solutions


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