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Remote Generative Ai Engineer Jobs in Stockbridge, GA

... and remote time to do your job most effectively. Job Responsibility In this role, you will ... Have demonstrated experience with Generative AI assisted development tools like Cursor, Windsurf ...

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing

Senior Product Manager

Atlanta, GA · Remote

$150K - $200K/yr

Hands-on experience with modern generative AI technologies, including prompt engineering, retrieval ... This position operates in a remote environment with frequent use of computers and office equipment.

Senior Product Manager

Atlanta, GA · On-site +1

$121K - $160K/yr

Hands-on experience with modern generative AI technologies, including prompt engineering, retrieval ... This position operates in a remote environment with frequent use of computers and office equipment.

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Knowledge of Generative AI technologies, including Large Language Models (LLMs), Retrieval ...

Location- Hybrid (3 days in office, 2 days remote): Atlanta, GA, Columbus, GA or Jacksonville, FL ... Knowledge of Generative AI technologies, including Large Language Models (LLMs), Retrieval ...

Showing results 21-40

Remote Generative Ai Engineer information

See Stockbridge, GA salary details

$32.4K

$98.8K

$163.3K

How much do remote generative ai engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote generative ai engineer in Stockbridge, GA is $98,805.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,800.00 and $129,200.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What job categories do people searching Remote Generative Ai Engineer jobs in Stockbridge, GA look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Stockbridge, GA are:

What cities near Stockbridge, GA are hiring for Remote Generative Ai Engineer jobs?

Cities near Stockbridge, GA with the most Remote Generative Ai Engineer job openings:

Lead AI Security Architect 2026 - US

Aimpoint Digital

Atlanta, GA • On-site, Remote

$62.50 - $80.75/hr

Full-time

Re-posted 13 days ago


Job description

Are you an experienced security engineer / architect looking to apply your strategic mindset to help customers securely adopt enterprise AI tools, modernize security architectures and govern the risks introduced by generative AI platforms, AI assistants, coding copilots and LLM-enabled applications?

Aimpoint Digital is a fully remote, rapidly growing AI and Data Engineering consultancy; specializing in enabling tangible business outcomes and ROI for organizations around the globe. AI is fundamentally changes how the world works, and our philosophy toward AI security is a combination of mitigating risk without slowing innovation. What sets us apart is our track record of providing strategic advisory services alongside unmatched delivery expertise.

What you will do

In this position, you will be a crucial member in shaping the future of AI; specifically, by enabling designing scalable security architectures that enable organizations to innovate both quickly, and securely. You will design and implement security solutions enable customers to securely deploy, and govern, Claude Enterprise.

You will:

  • Assess existing security, identity, data, cloud and SaaS architectures and advise on best-in-class solutions for securing enterprise AI tooling across customers in a wide range of industries
  • Conduct comprehensive evaluations of AI tools (e.g. Claude, Claude Enterprise), platform configurations, data access patterns, connector usage, security controls, processes and personnel to deliver informed recommendations leveraging your expertise in security engineering and AI governance
  • Design and implement security controls for enterprise AI platforms, including SSO, SCIM, RBAC, MFA, conditional access, admin roles, user lifecycle management, retention policies, audit logging, workspace controls, DLP, and acceptable-use enforcement
  • Assess and govern AI platform features such as file uploads, custom assistants, projects, GPTs, connectors, browsing, code execution, data analysis, plugins, agents, API access, and external sharing
  • Review and secure AI integrations with enterprise repositories and collaboration platforms, including Google Drive, SharePoint, OneDrive, Slack, Teams, GitHub, GitLab, Jira, Confluence, Salesforce, Snowflake, Databricks, and BI platforms
  • Manage and lead end-to-end AI Security Implementation efforts as part of a project team; including activities such as identity integration, access control design, data protection controls, AI platform configurations, connector governance, monitoring / logging and incident response workflows

Who you are

We are building a diverse team of talented and motivated people who deeply understand business problems and enjoy solving them. You are a self-starter who is passionate about responsibly deploying AI solutions. You understand that AI Security isn't a nice to have, it's a pre-requisite for enabling AI solutions at scale. Specifically, scale that enables business value without exposing organizations to unnecessary risk.

As an AI Security Architect, you will be expected to own and manage client engagements, take part in the development of our AI Security practice, aid in business development and contribute innovative ideas and initiatives to Aimpoint Digital.

Baseline skills requirements include, though are not limited to:

  • Degree in Computer Science, Cyber Security, Information Systems, Engineering, or equivalent experience
  • Strong written and verbal skills; specifically with respect to C-Suite / Executive communication
  • Experience designing and delivering enterprise security architectures (projects or otherwise), particularly across Cloud, SaaS, data, application or security operations
  • Experience securing SaaS platforms using SSO, SCIM, RBAC, MFA, conditional access, logging DLP, lifecycle management and administrative controls
  • Experience working with identity providers and collaboration platforms like Okta, Microsoft Entra, Google Workspace, Microsoft 365, Slack, Atlassian, GitHub and/or GitLab
  • Experience working with Cloud Platforms such as AWS, Azure and/or GCP
  • Experience with secure SDLC, application security testing, API security, secrets management, vulnerability management and software supply chain (this is a must-have)
  • Experience performing threat modelling and translating risk into practical technical and operational controls
  • Experience integrating security telemetry into SIEM/SOAR platforms such as Splunk, Sentinel, Datadog or similar technologies
  • 5+ years experience in security engineering, cloud security, application security, data security, IAM, security architecture or security operations
  • 5+ years experience working with cloud / enterprise SaaS platforms or modern data platforms (specifically Databricks / Snowflake / Fabric / Big Query)
  • Experience with generative AI platforms; Claude Enterprise specifically
  • Familiarity with LLM security risks such as prompt injection, sensitive information disclosure, insecure output handling, excessive agency, retrieval abuse and software supply chain risk
  • Familiarity with AI security and governance frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, ISO 42001, SOC 2, HIPAA, PCI DSS, GDPR, or similar frameworks is desirable
  • Experience with Python, APIs, Terraform, CI/CD pipelines, GitHub Actions, GitLab CI, container technologies, or infrastructure-as-code security is desirable
  • Experience conducting AI red teaming, adversarial testing, abuse-case analysis, or model-integrated application security reviews is desirable
  • Advanced certification in one or more cloud platforms, such as AWS, Azure, or GCP, is desirable
  • Security certifications such as CISSP, CCSP, CISM, GIAC, AWS Security Specialty, Azure Security Engineer, Google Professional Cloud Security Engineer, or similar credentials are desirable

This position is fully-remote; however, Atlanta-based applicants will have the opportunity to work in our headquarters in Sandy Springs, GA.

Employment Type: FULL_TIME