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Remote Generative Ai Jobs in Atlanta, GA (NOW HIRING)

... remote POSITION OVERVIEW: The Sr. IAM AI Solutions Achitect is responsible for two things. First, making sure that as Newell builds and adopts agentic and generative AI solutions, those solutions are ...

Senior eDiscovery Analyst

Atlanta, GA · Remote

$88K - $112K/yr

This is a remote-first position, with a focus on candidates in GA, TX, MA, IL, DE, MN, NY, and DC ... Serve as a subject-matter resource for generative AI and analytics tools, mentoring analysts and ...

This role is fully remote, with no regular in-office requirement. The Contributions You'll Make ... Experience building and supporting enterprise-scale generative AI solutions. * Experience with ...

Experience designing and deploying Generative AI solutions using LLMs, RAG architectures, vector ... Travel: While this is a remote position, occasional travel to Humana's offices for training or ...

Experience designing and deploying Generative AI solutions using LLMs, RAG architectures, vector ... Travel: While this is a remote position, occasional travel to Humana's offices for training or ...

Experience designing and deploying Generative AI solutions using LLMs, RAG architectures, vector ... Travel: While this is a remote position, occasional travel to Humana's offices for training or ...

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 information

See Atlanta, GA salary details

$15.4K

$142.6K

$183.7K

How much do remote generative ai jobs pay per year?

As of Sep 4, 2026, the average yearly pay for remote generative ai in Atlanta, GA is $142,550.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,900.00 and $161,100.00 per year, depending on experience, location, and employer.

What is a remote generative AI?

A Remote Generative AI job involves working with artificial intelligence systems that can create new content, such as text, images, or music, from data. These roles are performed remotely, allowing professionals to work from anywhere while developing, training, and deploying generative models like GPT or DALL-E. Job responsibilities may include data preparation, model training, evaluation, and integrating generative AI solutions into products or services. Professionals in this field often collaborate with teams online using cloud-based tools and communication platforms.

What skills and qualifications are needed to thrive as a remote generative AI specialist?

To thrive as a Remote Generative AI Specialist, you need strong expertise in machine learning, deep learning, and programming languages like Python, often supported by a degree in computer science or a related field. Proficiency with frameworks such as TensorFlow or PyTorch, cloud platforms, and relevant certifications (e.g., Google Cloud ML Engineer) is highly beneficial. Effective problem-solving, self-motivation, and clear communication are crucial for collaborating remotely and driving innovative AI solutions. These skills ensure you can develop, deploy, and improve generative AI models efficiently in distributed work environments.

What are common challenges faced by remote generative AI professionals and how can they be addressed?

Remote Generative AI professionals often face challenges such as collaborating effectively across time zones, ensuring data security, and staying updated with rapidly evolving AI technologies. To overcome these, it's important to establish clear communication channels, utilize version control and collaboration tools, and participate in regular team meetings. Additionally, investing time in continuous learning through online courses and AI research communities can help professionals stay current with industry advancements.

What is the difference between Remote Generative Ai vs Data Scientist?

AspectRemote Generative AiData Scientist
Required CredentialsKnowledge of AI/ML, programming skills, familiarity with NLP and deep learningStatistics, programming, data analysis, often a degree in CS, stats, or related fields
Work EnvironmentRemote, collaborative teams, AI research labs, tech companiesRemote or on-site, data analysis teams, research or business units
Industry UsageDeveloping AI models, creating generative content, NLP applicationsAnalyzing data, building predictive models, informing business decisions

Remote Generative Ai specialists focus on creating AI models that generate content, requiring expertise in AI/ML and programming. Data Scientists analyze data to extract insights and build models, often with similar technical backgrounds. While both roles may work remotely and in tech industries, their core functions differ: one develops generative AI systems, the other interprets data for strategic insights.

What are the best remote generative AI jobs?

Remote generative AI jobs include roles such as AI research scientist, machine learning engineer, and data scientist, focusing on developing and deploying AI models like GPT or DALL·E. These positions often require skills in programming, deep learning frameworks, and experience with large language models, with many opportunities available through tech companies, research institutions, and startups. They typically offer flexible schedules and may require certifications or advanced degrees in computer science or related fields.

What jobs can I get with remote generative AI?

Remote generative AI skills can qualify you for roles such as AI content developer, machine learning engineer, data scientist, or AI research scientist. These positions often require knowledge of AI frameworks, programming languages like Python, and experience with large language models or neural networks. Many of these jobs are available in tech companies, research institutions, and startups, often with flexible schedules and remote work options.

What are the most commonly searched types of Generative Ai jobs in Atlanta, GA?

The most popular types of Generative Ai jobs in Atlanta, GA are:

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

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

Infographic showing various Remote Generative Ai job openings in Atlanta, GA as of August 2026, with employment types broken down into 76% Full Time, 19% Part Time, and 5% Contract. Highlights an 71% Physical, 4% Hybrid, and 25% Remote job distribution, with an average salary of $142,550 per year, or $68.5 per hour.

Sr. IAM AI Solutions Architect

Newell Brands

Atlanta, GA • Remote

Full-time

Re-posted 27 days ago


Key responsibilities

  • Work with IAM tower leads to define and enforce access control policies for AI solutions, ensuring proper authorization and governance.

  • Collaborate with teams to build governance around non-human identities used in AI solutions, including provisioning, attestation, and lifecycle management.

  • Own the security and governance standards for agentic AI configuration layers, monitoring for configuration drift and unauthorized changes.


Newell Brands rating

7.3

Company rating: 7.3 out of 10

Based on 80 frontline employees who took The Breakroom Quiz

323rd of 545 rated manufacturers


Job description

Job ID: 14555 

Alternate Locations:  

Newell Brands is a leading consumer products company with a portfolio of iconic brands like Graco, Coleman, Oster, Rubbermaid, Sharpie and Yankee Candle - and 24,000 talented teammates around the world. Our culture is built on values in action: Integrity, Teamwork, Passion for Winning, Ownership, and Leadership. We work together to win, grow, and make a real impact-supported by a high-performing, inclusive, and collaborative environment where you can be your best, every day.

Job location: Atlanta, GA preferred but will consider remote

POSITION OVERVIEW:

The Sr. IAM AI Solutions Achitect is responsible for two things. First, making sure that as Newell builds and adopts agentic and generative AI solutions, those solutions are identity-safe. Users and AI agents should only access data and transactions they are authorized for, non-human identities need proper governance, and the configuration layers behind agentic AI (especially MCP and A2A) must be protected and well-managed. Second, finding practical ways to apply AI within the IAM program itself to build better integrations, increase delivery speed, and improve the experience for both our team and our end users.

This is not a tower ownership role. The IAM organization operates through established capability towers: IGA, PAM, AM, ILM, and others. This engineer works across all of them, bringing AI expertise and a cross-tower perspective. The day-to-day work happens in close partnership with tower leads and their engineers to define and build AI-related architecture and controls that fit each domain.


We view IAM as a business accelerator, not just a security function. When identity is well-architected for AI, the company can move faster with greater confidence. This person is responsible for keeping our IAM capabilities aligned with and actively supporting Newell's AI ambitions.

KEY RESPONSIBILITIES:

Pillar 1: Enabling Safe AI Development and Consumption

1. Access Governance for AI Solutions
Work with AM and IGA tower leads to define and enforce access control policies for agentic and generative AI solutions, keeping users and agents within their authorized scope.

Partner with tower engineers to design authorization models for AI-enabled applications. Entitlements should be scoped correctly and reviewed through each tower's existing governance processes.
Serve as a resource on AI identity architecture for business and IT teams building AI solutions. Engage the appropriate IAM towers early so controls are part of the design, not added after the fact.

2. Non-Human Identity Governance
Partner with IGA, ILM, and PAM towers to build governance around non-human identities (NHIs) used in AI solutions: agents, service accounts, machine identities, and automated workflows.
Work with ILM to define how NHIs are provisioned, attested, certified, rotated, and decommissioned. These should get the same lifecycle rigor as human identities.
Identify and remediate NHI sprawl, orphaned accounts, and over-privileged automated identities. Coordinate with PAM to confirm that secrets, tokens, and credentials are managed and rotated properly.

3. Agentic AI Configuration Governance (MCP & A2A)
Own the security and governance standards for MCP and A2A configuration layers, working with the AM and PAM towers on authentication, authorization boundaries, tool-use permissions, and logging.
Partner with IGA to govern agent-to-agent trust relationships, delegation scopes, and orchestration flows so they are authorized and auditable.
Work with IAM operations to monitor for configuration drift, unauthorized changes, and misconfigurations that could introduce identity or access risks.
Maintain documentation and operating procedures for agentic AI configuration controls in coordination with InfoSec and AI platform teams.

4. AI Identity Risk & Compliance
Work with tower leads and InfoSec to identify, assess, and address identity-related risks in AI architectures, covering authentication boundaries, authorization logic, and data access patterns.
Track the AI threat landscape, particularly around agent behavior anomalies, prompt injection attacks on identity controls, and unauthorized privilege escalation. Share findings with tower leads to inform their security posture.
Support audits and compliance activities related to AI identity governance, including access reviews, NHI inventories, and configuration attestations. Coordinate with Legal and Privacy as needed.

Pillar 2: Applying AI to Strengthen and Accelerate IAM

5. AI-Assisted Integration & Automation
Work with tower leads and engineers to identify where AI (agentic, generative, vibe coding, rapid prototyping) can improve integrations between IAM platforms and IT solutions.
Support tower teams in using AI-assisted development to accelerate the build-out of onboarding connectors, access request workflows, provisioning logic, and monitoring and alerting.

Prototype AI-driven automation that reduces manual effort in lifecycle processes, certifications, privileged access operations, and incident triage.
Evaluate AI-powered tools that could improve IAM operations, shorten integration timelines, or improve data quality, and bring recommendations to leadership.

6. IAM Program AI Guidance
Serve as the IAM program's primary resource on applying AI to improve security, delivery speed, and user experience. Work with each tower to apply AI in ways relevant to their domain.
Research and present emerging AI capabilities relevant to IAM: analytics, anomaly detection, intelligent access recommendations, natural language interfaces.
Develop playbooks and training so IAM staff across all towers can use AI tools effectively in their daily work, from prompt techniques to AI-assisted coding.
Establish development standards for AI-assisted IAM engineering so that quality, security, and consistency hold regardless of which tower does the work.

REQUIRED QUALIFICATIONS:

Experience in IAM, identity governance and related information security domains.
Strong understanding of authentication, authorization, access lifecycle management, and privileged access.
Broad knowledge of the IAM stack and how its components connect: client-server models, PAM, ILM, IGA, AM, and the dependencies between them.

Hands-on experience with AI/ML engineering, agentic frameworks, or rapid prototyping approaches like vibe coding.
Scripting or development skills (Python, JavaScript/TypeScript, or similar) for building IAM tooling and automation.
Working knowledge of agentic AI architecture, including MCP, A2A communication, orchestration patterns, and where identity controls fit in those layers.
Understanding of non-human identity types (AI agents, service accounts, machine identities) and the governance challenges they create.
Experience with or strong aptitude for AI-assisted development, including the use of generative AI tools for prototyping, building integrations, and solving technical problems.
Awareness of AI-specific security risks: how agentic and generative AI architectures introduce new attack surfaces for authentication, authorization, and access governance.
Hands-on experience with IAM platforms in hybrid or cloud environments.
Experience working in a matrixed or tower-based model where you drove outcomes through influence and partnership, not direct ownership.
Able to translate complex identity concepts into plain language for developers, business teams, and leadership.
Comfortable balancing innovation with risk, with an orientation toward finding a safe path to yes rather than defaulting to no.
Self-directed and able to manage multiple priorities without close supervision.

PREFERRED QUALIFICATIONS:

Experience securing AI-enabled platforms or workflows in an enterprise setting.
Familiarity with AI-driven analytics, anomaly detection, or intelligent recommendations in an IAM context.
Knowledge of machine identity frameworks (SPIFFE/SPIRE) and modern auth standards (OIDC, OAuth 2.0, SAML, SCIM).
Experience with audit, compliance, or regulatory stakeholders.
Relevant certifications: CISSP, CISM, or vendor-specific IAM certs.

EDUCATION:

Bachelor's degree in Information Security, Computer Science, Information Systems, or a related field, or equivalent professional experience. Demonstrated expertise and a strong delivery track record are valued equally.

WHO YOU ARE:

You're naturally curious about AI and identity security, and you stay current because the space interests you, not because it's a requirement. You enjoy learning new things and you're just as motivated to teach what you've learned to others. Change and ambiguity don't slow you down; they're part of what drew you to this kind of work.

You see IAM as something that enables the business to move, not something that holds it back. When someone brings you an AI use case, your first instinct is to figure out how to make it work safely. You're a builder. You'd rather prototype three approaches than spend the same time explaining why something is difficult.

You recognize that the work done in this role directly affects how quickly Newell can adopt AI across the enterprise, and that responsibility is something you take seriously.

Newell Brands (NASDAQ: NWL) is a leading global consumer goods company with a strong portfolio of well-known brands, including Rubbermaid, Sharpie, Graco, Coleman, Rubbermaid Commercial Products, Yankee Candle, Paper Mate, FoodSaver, Dymo, EXPO, Elmer's, Oster, NUK, Spontex and Campingaz. We are focused on delighting consumers by lighting up everyday moments. Newell Brands and its subsidiaries are Equal Opportunity Employers and comply with applicable employment laws. EOE/M/F/Vet/Disabled are encouraged to apply. 


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About Newell Brands

Sourced by ZipRecruiter

Newell Brands (NASDAQ: NWL) is a leading global consumer goods company with a strong portfolio of well-known brands, including Rubbermaid, Sharpie, Graco, Coleman, Rubbermaid Commercial Products, Yankee Candle, Paper Mate, FoodSaver, Dymo, EXPO, Elmer's, Oster, NUK, Spontex and Campingaz.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

Year founded

1903

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