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Full Time Mid Level Ai Engineer Jobs in Georgia (NOW HIRING)

Senior AI Engineer

Atlanta, GA

$100K - $138K/yr

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 ...

Senior AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

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 ...

We are seeking a highly skilled and forward-thinking AI Engineer to join our AI Engineering team ... Ability to work proactively with a high level of initiative and accuracy. * Ability to manage ...

AI Engineer

Atlanta, GA · On-site +1

... CI-level quality gates. • Support document AI capabilities -- working with parsing, extraction ... UNAVAILABLEEmployment Type: FULL_TIME

\n \n \n \n \n Our client, a growing tech company based in Ireland is looking to bring on a mid level PHP Developer on a fully remote, rolling contract. \n \n \n \n \n \n Requirements \n \n \n * 2 ...

AI Engineer

Atlanta, GA · On-site

$50K - $112K/yr

Industry/Sector Not Applicable Specialism IFS - Information Technology (IT) Management Level Associate & Summary The Opportunity As an AI Engineer, you will be at the forefront of transforming raw ...

Mid-Level UI developer

Atlanta, GA · On-site

$48 - $62.50/hr

I have an opportunity for a " Mid-Level UI Developer " - ( Atlanta, GA - Onsite) and I am looking for a candidate who can join Immediately if you are interested, reply to me with your updated resume ...

... (full-time employment) * Proficiency in at least one of: Java, C#, Python, or JavaScript/Node.js ... Paid, enterprise-level AI engineering training and certification - you earn while you learn

Senior AI Engineer

Alpharetta, GA · On-site

$119K - $157K/yr

Senior AI Engineer Location: Alpharetta, GA and NYC Duration ... Fulltime Key Responsibilities * Design, build, and deploy Python-based AI/LLM applications using ...

Distinguished AI Engineer Distinguished AI Engineer Location: This role requires associates to be ... Job Level: Non-Management Exempt Workshift: Job Family: IFT > IT Architecture Please be advised ...

AI Engineer - Operations

Alpharetta, GA · On-site

$67K - $91K/yr

We are looking to add our second AI Engineer to our Platform and Innovation R&D team to lead how we ... Coffee bar with cold brew on tap and a full time barista * Standing desk (if you're into that sort ...

Lead AI Engineer

Alpharetta, GA

$100K - $131K/yr

Job Title Lead AI Engineer About Your Role As a Lead AI Engineer, you will play a critical role in ... level across multiple teams * 4+ years of experience building andmaintainingCI/CD pipelines and ...

Senior AI Engineer

Atlanta, GA · Hybrid

$100K - $138K/yr

Senior AI Engineer Senior AI Engineer Location: This role requires associates to be in-office 1-2 ... Job Level: Non-Management Exempt Workshift: Job Family: IFT > Artificial Intelligence Please be ...

Senior AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior AI Engineer Senior AI Engineer Location: This role requires associates to be in-office 1-2 ... Job Level: Non-Management Exempt Workshift: Job Family: IFT > Artificial Intelligence Please be ...

Senior AI Engineer

Atlanta, GA

$100K - $138K/yr

Production-quality Python at engineering level -- testing, code review, version control fluency ... mid-market enterprises to large public-sector and commercial organizations. Founded in 2011 ...

WSP is currently initiating a search for a Mid-Senior Level Civil Engineer for our Power Delivery Substation Civil/Structural Group to perform engineering design for electrical substations for our ...

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Full Time Mid Level Ai Engineer information

What is a full time mid level AI engineer?

A Full Time Mid Level AI Engineer is a professional who works on developing, implementing, and optimizing artificial intelligence models and systems in a full-time capacity. At the mid-level, they typically have a few years of experience and are proficient in programming languages like Python, as well as machine learning frameworks such as TensorFlow or PyTorch. Their responsibilities often include building and training models, analyzing data, collaborating with other engineers or data scientists, and deploying AI solutions to solve real-world problems. They also contribute to code reviews, documentation, and may mentor junior team members.

What are the key skills and qualifications needed to thrive as a full time mid level AI engineer?

To thrive as a Full Time Mid Level AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with data modeling. Proficiency in programming languages like Python, familiarity with machine learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms are typically required. Problem-solving abilities, strong communication, and teamwork skills help you effectively collaborate and translate complex technical ideas. These skills ensure you can develop, deploy, and maintain AI solutions that drive business value and innovation.

What are some common challenges faced by mid level AI engineers in full time roles, and how can they be managed?

Mid-level AI engineers often encounter challenges such as balancing project deadlines with the complexity of developing and deploying machine learning models, integrating AI solutions with existing systems, and managing ambiguous problem statements. Navigating these challenges typically involves effective communication with cross-functional teams, time management, and continuous learning to stay updated on the latest AI frameworks and best practices. Proactively seeking mentorship and participating in code reviews can also help refine technical skills and facilitate smoother project execution.

What is the difference between Full Time Mid Level Ai Engineer vs Data Scientist?

AspectFull Time Mid Level Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping AI models, deploying algorithms, collaborating with engineering teamsAnalyzing data, building predictive models, creating reports for business insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, tech industries

Full Time Mid Level Ai Engineers focus on developing and deploying AI models within technical teams, while Data Scientists analyze data to generate insights. Both roles require similar educational backgrounds and often collaborate, but their core responsibilities differ in application and focus.

Are full time mid level AI engineers in high demand?

Full-time mid-level AI engineers are in high demand due to the rapid growth of artificial intelligence applications across industries. Employers seek professionals with skills in machine learning, deep learning, and programming languages like Python, often requiring experience with frameworks such as TensorFlow or PyTorch. This demand is expected to continue as AI adoption expands in sectors like healthcare, finance, and technology.

How much do full time mid level AI engineers make?

Full-time mid-level AI engineers typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Salaries can increase with specialized skills in machine learning frameworks, programming languages, and data handling tools.

What are popular job titles related to Full Time Mid Level Ai Engineer jobs in Georgia?

For Full Time Mid Level Ai Engineer jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Full Time Mid Level Ai Engineer jobs in Georgia look for?

The top searched job categories for Full Time Mid Level Ai Engineer jobs in Georgia are:

Infographic showing various Full Time Mid Level Ai Engineer 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.

$100K - $138K/yr

Full-time

Re-posted 21 days 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