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Ai Solutions Engineer Jobs in Decatur, GA (NOW HIRING)

Job Overview The Adv, AI Solutions Engineer is a hands-on technical role within Mercedes-Benz USA (MBUSA) Information Technology. You will partner with business and technology teams to identify high ...

AI Solutions Engineer Lead

Atlanta, GA ยท Hybrid

$98K - $129K/yr

AI Solutions Engineer Lead AI Solutions Engineer Lead Location: This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing ...

Job Overview The Adv, AI Solutions Engineer is a hands-on technical role within Mercedes-Benz USA (MBUSA) Information Technology. You will partner with business and technology teams to identify high ...

AI Solutions Engineer Lead

Atlanta, GA ยท Hybrid

$98K - $129K/yr

AI Solutions Engineer Lead Location: This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity ...

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Ai Solutions Engineer information

See Decatur, GA salary details

$43.4K

$120.4K

$177.2K

How much do ai solutions engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for ai solutions engineer in Decatur, GA is $120,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,100.00 and $137,200.00 per year, depending on experience, location, and employer.

What is an AI Solutions Engineer?

AI Solutions Engineers are professionals who design, develop, and implement artificial intelligence-based systems and applications to solve business problems. They bridge the gap between AI research and practical deployment, working closely with data scientists, software engineers, and business stakeholders. Their responsibilities often include creating AI models, integrating them into products or workflows, and ensuring these solutions are scalable, reliable, and aligned with organizational goals.

How does an AI Solutions Engineer typically collaborate with cross-functional teams during a project lifecycle?

AI Solutions Engineers frequently work alongside data scientists, software developers, product managers, and business stakeholders throughout a project's lifecycle. Their role involves translating business requirements into technical AI solutions, integrating models into existing systems, and ensuring seamless deployment. Regular communication and collaboration are essential, as they often lead technical discussions, clarify project goals, and address implementation challenges. This cross-functional teamwork fosters innovation and ensures that AI solutions are practical, scalable, and aligned with business objectives.

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

To thrive as an AI Solutions Engineer, you need a strong background in computer science, machine learning, and data analytics, typically supported by a relevant degree and experience with AI frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, Azure, or GCP), and proficiency in programming languages like Python are essential, along with certifications in AI or cloud technologies. Excellent problem-solving, communication, and teamwork skills help you translate business needs into technical solutions and collaborate across departments. These competencies ensure effective development, deployment, and integration of AI solutions that drive business value.

What is the difference between Ai Solutions Engineer vs Data Scientist?

AspectAi Solutions EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong statistical and programming skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teams, implements models in productionAnalyzes data, builds models, interprets results for insights
Employer & Industry UsageTech companies, AI-focused firms, startupsResearch institutions, tech companies, finance, healthcare

While both roles involve AI and data, Ai Solutions Engineers focus on deploying AI solutions in production environments, working closely with engineering teams. Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their focus on implementation versus analysis.

What are popular job titles related to Ai Solutions Engineer jobs in Decatur, GA?

For Ai Solutions Engineer jobs in Decatur, GA, the most frequently searched job titles are:

What job categories do people searching Ai Solutions Engineer jobs in Decatur, GA look for?

The top searched job categories for Ai Solutions Engineer jobs in Decatur, GA are:

What cities near Decatur, GA are hiring for Ai Solutions Engineer jobs?

Cities near Decatur, GA with the most Ai Solutions Engineer job openings:

Infographic showing various Ai Solutions Engineer job openings in Decatur, GA as of August 2026, with employment types broken down into 83% Full Time, 12% Part Time, and 5% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $120,366 per year, or $57.9 per hour.

AI Solutions Engineer

Norcross, GA โ€ข On-site

Full-time

Posted 6 days ago


Job description

Position Summary

The AI Solutions Engineer translates business needs into secure, build-ready specifications for AI-enabled software, workflows, and process automations. Working closely with departmental subject-matter experts, this position strengthens business requirements, identifies gaps and risks, guides AI-assisted development, and validates completed solutions.

This hands-on, consultative role supports internal solutions such as dashboards, CRM functionality, accounting automation, system integrations, and agentic workflows. The position also develops employees participating in the company's AI-enabled development process by improving their requirements-development, process-analysis, and AI skills.

Essential Duties and ResponsibilitiesRequirements and Solution Design
  • Partner with subject-matter experts to define business problems, desired outcomes, workflows, and solution requirements.
  • Review business requirements documents for completeness, accuracy, feasibility, and alignment with intended business outcomes.
  • Identify missing requirements, assumptions, dependencies, process exceptions, data requirements, user roles, system states, and potential risks.
  • Document current-state and future-state processes and recommend opportunities to simplify or improve workflows.
  • Convert validated business requirements into detailed technical and functional specifications suitable for AI-assisted development.
  • Translate technical limitations and options into clear language that business users can understand and act upon.
  • Ensure proposed solutions align with established business processes, internal controls, and organizational priorities.
AI-Assisted Solution Delivery
  • Direct AI-assisted development using approved specifications, tools, and development practices.
  • Review completed solutions against approved requirements and acceptance criteria.
  • Coordinate user validation, document deficiencies, and guide subsequent revisions.
  • Investigate gaps between delivered functionality and business requirements and determine whether corrections are needed in the requirements, specifications, tools, or implementation.
  • Remain engaged throughout the solution lifecycle, from initial discovery through implementation and post-delivery refinement.
  • Improve the templates, prompts, standards, and methods used to move solutions from initial request to implementation.
Employee Coaching and Enablement
  • Coach designated departmental employees, known internally as Flowgrammers, in requirements development, process analysis, and effective use of AI tools.
  • Provide constructive technical feedback while maintaining the subject-matter expert's ownership of the business solution.
  • Develop reusable templates, guides, skills, and tools that help employees produce complete and reliable requirements.
  • Teach employees how to assemble relevant context, evaluate AI-generated output, break complex problems into manageable tasks, and refine work through iteration.
  • Evaluate work products against established proficiency standards and recommend development opportunities.
  • Identify recurring weaknesses and opportunities across departments and create initiatives that improve the overall quality of AI-enabled solution development.
AI Tooling, Integrations, and Governance
  • Define the system access, data access, business rules, and permissions required for AI-enabled tools, agents, and workflows.
  • Design limited-access models that provide only the permissions necessary to complete an approved business function.
  • Prepare detailed tooling and permission requirements for review under established internal controls.
  • Collaborate with technical engineers responsible for building and deploying backend tools, connectors, and system integrations.
  • Evaluate APIs, databases, enterprise platforms, authentication methods, and data flows to determine solution feasibility and risk.
  • Monitor developments in AI technology and recommend appropriate updates to internal practices, tools, and standards.
Required Qualifications
  • Experience analyzing business processes and translating business needs into functional or technical requirements.
  • Demonstrated ability to identify incomplete requirements, unaddressed exceptions, dependencies, data implications, and operational risks.
  • Experience writing clear, detailed specifications for software, workflow automation, or AI-assisted development.
  • Working knowledge of large language models, AI agents, and the capabilities and limitations of generative AI.
  • Understanding of APIs, databases, authentication, system integrations, and data flows.
  • Ability to use a scripting language such as Python for analysis, prototyping, integration support, or troubleshooting.
  • Strong analytical, problem-solving, written communication, and documentation skills.
  • Ability to communicate effectively with technical and nontechnical stakeholders.
  • Demonstrated ability to coach others, deliver constructive feedback, and support organizational change.
  • Ability to manage multiple initiatives and remain engaged from requirements gathering through delivery.