AI Solutions Engineer Jobs in Georgia
AI Solutions Engineer jobs in Georgia are in strong demand, concentrated in enterprise technology, financial services, healthcare IT, and defense contracting, with openings from entry-level associate roles through senior and principal positions. Atlanta is the dominant hiring hub, followed by growing activity in Alpharetta and Augusta, where employers like NCR Voyix, Cox Enterprises, and Leidos maintain significant Georgia operations. The most sought-after specialties in the state are cloud-native AI deployment, MLOps pipeline development, and large language model integration for enterprise clients. Find a role that fits below and apply directly.
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In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; Kirkland, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 10 years of experience with data center technologies, solutions and their deployment..
- Experience with data center networking, such as routing, switching, DNS, and IP addressing; compute and storage concepts; and operations including power, cooling, and procedures.
- Experience with AI model training and inference, deploying OSS frameworks such as PyTorch, Jax, etc., and optimizing performance versus costs.
- Experience with scripting and coding in Python, YAML, and Kubernetes.
Preferred qualifications:
- Experience training and fine tuning large models with accelerators.
- Experience with performance profiling and benchmarking tools (i.e., MLPerf, PyTorch profiler, Tensorboard).
- Experience deploying compute, network and storage solutions in data centers. Experience deploying TPU clusters.
About the job
As an AI Infrastructure Field Solution Architect, your experience and thought leadership will support Google Cloud commercial teams to incubate, pilot, and roll out industry-leading TPU and GPU hardware at market innovators, large enterprises, and early-stage startups. You will empower accounts to innovate faster with systems and software using our latest technical offerings.
You will guide technical discussions on network topologies, fabric architecture, and compute or storage integration, while supporting server and cluster provisioning. This includes on-site visits to client hosting facilities during physical implementation.
You will identify and assess opportunities, evaluating cost-to-performance tradeoffs, evaluating baseline models, developing migration paths, and integrating specialized silicon into overarching technical roadmaps. Along the way, you will partner closely with internal product and engineering units to remove roadblocks and shape future platform capabilities.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $233000 - $324000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Act as a trusted advisor to customers, helping them understand and incorporate AI accelerators into their overall business strategy by designing training and inferencing platforms, and incorporating customers' existing data center technologies.
- Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on Proofs of Concept, demonstrating features, optimizing model performance, profiling, and benchmarking.
- Assist in production deployment of Google Cloud accelerators, troubleshoot integration issues with existing compute, networking, and storage solutions, and enable customers to operate their training and inferencing clusters successfully.
- Build repeatable assets to enable other customers and internal teams.
- Collaborate with the AI Infrastructure Dedicated Engineering Team in Google Compute Engine, and scale ML techniques and solutions broadly. Influence Google Cloud strategy at the intersection of infrastructure and AI by advocating for enterprise customer requirements.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; Kirkland, WA, USA; New York, NY, USA.
Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 10 years of experience with data center technologies, solutions and their deployment..
- Experience with data center networking, such as routing, switching, DNS, and IP addressing; compute and storage concepts; and operations including power, cooling, and procedures.
- Experience with AI model training and inference, deploying OSS frameworks such as PyTorch, Jax, etc., and optimizing performance versus costs.
- Experience with scripting and coding in Python, YAML, and Kubernetes.
Preferred qualifications:
- Experience training and fine tuning large models with accelerators.
- Experience with performance profiling and benchmarking tools (i.e., MLPerf, PyTorch profiler, Tensorboard).
- Experience deploying compute, network and storage solutions in data centers. Experience deploying TPU clusters.
About the job
As an AI Infrastructure Field Solution Architect, your experience and thought leadership will support Google Cloud commercial teams to incubate, pilot, and roll out industry-leading TPU and GPU hardware at market innovators, large enterprises, and early-stage startups. You will empower accounts to innovate faster with systems and software using our latest technical offerings.
You will guide technical discussions on network topologies, fabric architecture, and compute or storage integration, while supporting server and cluster provisioning. This includes on-site visits to client hosting facilities during physical implementation.
You will identify and assess opportunities, evaluating cost-to-performance tradeoffs, evaluating baseline models, developing migration paths, and integrating specialized silicon into overarching technical roadmaps. Along the way, you will partner closely with internal product and engineering units to remove roadblocks and shape future platform capabilities.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $233000 - $324000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Act as a trusted advisor to customers, helping them understand and incorporate AI accelerators into their overall business strategy by designing training and inferencing platforms, and incorporating customers' existing data center technologies.
- Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on Proofs of Concept, demonstrating features, optimizing model performance, profiling, and benchmarking.
- Assist in production deployment of Google Cloud accelerators, troubleshoot integration issues with existing compute, networking, and storage solutions, and enable customers to operate their training and inferencing clusters successfully.
- Build repeatable assets to enable other customers and internal teams.
- Collaborate with the AI Infrastructure Dedicated Engineering Team in Google Compute Engine, and scale ML techniques and solutions broadly. Influence Google Cloud strategy at the intersection of infrastructure and AI by advocating for enterprise customer requirements.
See All 26 AI Solutions Engineer Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
Find AI Solutions Engineer JobsAI Solutions Engineer Jobs by City in Georgia
Where Georgia roles are concentrated, by current openings.
AI Solutions Engineer Job Market in Georgia
A snapshot from current Georgia openings, updated as new roles post.
Who's Hiring
What Georgia Employers Look For
The qualifications that appear most often in AI solutions engineer jobs across Georgia.
- Bachelor's or master's degree in computer science, AI, or a related engineering field
- Hands-on experience building and deploying machine learning models in production environments
- Proficiency with cloud platforms such as AWS, Google Cloud, or Azure for AI workloads
- Strong programming skills in Python and familiarity with frameworks like TensorFlow or PyTorch
- Ability to translate complex AI capabilities into client-facing solutions and technical presentations
- Experience with MLOps tooling, CI/CD pipelines, and model monitoring in enterprise settings
AI Solutions Engineer Jobs in Georgia: Frequently Asked Questions
How do you become a ai solutions engineer in Georgia?
Becoming an ai solutions engineer in Georgia does not require a state-issued license, so the path runs through education and demonstrated technical skill. Most Georgia employers expect at least a bachelor's degree in computer science, data science, or a related field, though many also hire candidates with strong portfolios from bootcamps or self-study. Industry certifications from AWS, Google Cloud, or Microsoft Azure carry real weight with Georgia hiring managers, particularly in Atlanta's dense technology and financial services sector.
How much do AI solutions engineers make in Georgia?
AI solutions engineers in Georgia earn a median of about $131,010 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $80,110 for the lowest 10% to over $176,000 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai solutions engineers in Georgia?
Employers hiring ai solutions engineers in Georgia right now include Amazon Web Services, Fisher & Phillips LLP, and NCR, based on current listings on Migrate Mate as of November 2026. Georgia's mix of Fortune 500 headquarters, large defense contractors, and a fast-growing technology corridor along the GA-400 corridor gives the state a particularly varied employer base for this role.
Which Georgia cities have the most ai solutions engineer jobs?
Atlanta, Warner Robins, and Georgia have the most ai solutions engineer openings in Georgia. Atlanta anchors the market through its concentration of enterprise technology firms, financial institutions, and corporate headquarters, while Alpharetta's technology park and Augusta's defense and cybersecurity presence pull significant hiring activity into those suburban and secondary markets.
Are there remote ai solutions engineer jobs in Georgia?
Yes, and more than most fields. About 100% of ai solutions engineer openings tied to Georgia are remote or hybrid as of November 2026, reflecting how much of the role involves software development, model training, and client consultation that translates well to distributed work. The portions most likely to require in-person presence are on-site client implementations and regulated enterprise environments.
How can I get hired as a ai solutions engineer in Georgia with little or no experience?
The most realistic entry path is a junior or associate solutions engineer role at one of Georgia's large technology consultancies or cloud resellers, where structured onboarding programs are common. Georgia Tech's co-op program and Kennesaw State's applied computing pipeline feed directly into Atlanta-area employers. Candidates transitioning from data analyst, software developer, or IT consultant roles find the move natural, and earning an entry-level cloud certification from AWS or Google before applying gives your application a concrete technical signal.
Where can I find and apply to ai solutions engineer jobs in Georgia?
You can find and apply to ai solutions engineer jobs in Georgia on Migrate Mate, which lists current Georgia openings across Atlanta, Alpharetta, Augusta, and other markets in the state. Find the roles that fit your experience and apply directly from the listing.
See All 26 AI Solutions Engineer Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
Find AI Solutions Engineer Jobs