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Explainable Ai Jobs in Georgia (NOW HIRING)

Bricklayer AI

Quality & Release Engineering Leader

Atlanta, GA · On-site

$69K - $89K/yr

... AI-powered capabilities remain predictable, explainable, and trustworthy • Develop performance, scalability, resiliency, and load-testing programs • Validate platform behavior under production ...

State Farm

Lead GenAI Engineer (LLM)

Dunwoody, GA · Hybrid

$101K - $133K/yr

We work at the frontier of large language models, agentic architectures, and cloud-native AI -- delivering solutions that are reliable, explainable, and that enhance human decision making. Join us if ...

Workday

Senior/Principal AI Engineer

Atlanta, GA

$120K - $166K/yr

... explainable, and built to operate at global scale. About You P5, Principal Machine Learning /AI ... Engineer Basic Qualifications * 10+ years experience as a member of a data science, machine ...

Workday, Inc.

Senior/Principal AI Engineer

Atlanta, GA · On-site

$120K - $166K/yr

... explainable, and built to operate at global scale. About You P5, Principal Machine Learning /AI ... Engineer Basic Qualifications * 10+ years experience as a member of a data science, machine ...

Hearst

Head of Residual Strategy

Lawrenceville, GA

... explainable, and trusted by the market. Operating at the intersection of data science, domain ... Experience working with production AI/ML systems What This Role Is Not * Not a pure data science ...

Hearst

Head of Residual Strategy

Lawrenceville, GA

... explainable, and trusted by the market. Operating at the intersection of data science, domain ... Experience working with production AI/ML systems What This Role Is Not * Not a pure data science ...

Hearst

Head of Residual Strategy

Lawrenceville, GA

... explainable, and trusted by the market. Operating at the intersection of data science, domain ... Experience working with production AI/ML systems What This Role Is Not * Not a pure data science ...

Booz Allen Hamilton

AL/ML Technical Lead

Atlanta, GA · On-site

$128.70 - $292/hr

... explainable, secure, and compliant with public health data privacy and ethical standards. This position is located in Atlanta, GA. Responsibilities * Lead the design and development of scalable AI ...

Booz Allen Hamilton

AL/ML Technical Lead

Atlanta, GA · On-site

As an AI / ML Technical Lead, you will define and drive the technical direction of mission-critical ... You will ensure systems are performant, explainable, secure, and compliant with public health data ...

Booz Allen Hamilton

AL/ML Technical Lead

Atlanta, GA · On-site

... explainable, secure, and compliant with public health data privacy and ethical standards.This positionis located inAtlanta, GA. What You'll Work On: * Lead the design and development of scalable AI ...

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Explainable Ai information

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.

What are the key skills and qualifications needed to thrive as an Explainable AI specialist?

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

What are popular job titles related to Explainable Ai jobs in Georgia?

For Explainable Ai jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Explainable Ai jobs in Georgia look for?

The top searched job categories for Explainable Ai jobs in Georgia are:

What cities in Georgia are hiring for Explainable Ai jobs?

Cities in Georgia with the most Explainable Ai job openings:

Explainable Ai jobs near you
Infographic showing various Explainable Ai 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.

Product Management Lead, AI

Magnet Forensics

Atlanta, GA • On-site

Full-time

Medical, Retirement

Re-posted 29 days ago

Job description

Who We Are; What We Do; Where We're Going
 
Magnet Forensics is a global leader in the development of digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices. We are continually innovating so our customers can deploy advanced and effective tools to protect their companies, communities, and countries.
 
Serving thousands of customers globally, our solutions are playing a crucial role in modernizing digital investigations, helping investigators fight crime, protect assets, and guard national security.
 
With employees based around the world, Magnet Forensics has been expanding our global presence. As a part of Magnet Forensics, you can expect to make a difference in the world, no matter what role you play. You'll be supported through learning and development, not to mention an incredible team with unbelievable talent and integrity.
 
If you think you would be the right person to join our team working towards this goal, we would love to hear from you! 

Role Overview 
Magnet Forensics is building the next generation of AI-native, agentic capabilities across our digital forensics and incident response (DFIR) portfolio. This role is your opportunity to define and ship agentic experiences that change how investigators, examiners, and analysts do their most important work. 
 
As Product Management Lead, Agentic AI, you will drive the strategy and execution for agentic product experiences across the Magnet portfolio. You will turn fast-moving AI capabilities into trusted, governed products across the entire Magnet One platform that delivers measurable value, partnering closely with customers, engineering, design, data science, and go-to-market teams. You have already built agentic experiences elsewhere, and you will help us do the same here, at the scale and trust bar that forensic work demands. 
 
This is a high-impact individual contributor role for a builder who is energized by frontier AI, comfortable with ambiguity, and focused on adoption, growth, and outcomes that show up in the data.
What You'll Do
  • Drive the agentic strategy: Drive the product vision, roadmap, and success metrics for agentic experiences across the portfolio, from focused agent workflows to full orchestration. 
  • Build agentic experiences that ship: Design and deliver AI-native products (agents, copilots, human-in-the-loop workflows, tool use, retrieval, and reasoning) that are reliable, explainable, and production grade. 
  • Make autonomy trustworthy: Treat governance as an enforced constraint, not an aspiration. Define hard limits, output verification, reversibility, escalation paths, and auditability so users can trust what an agent does on their behalf. 
  • Drive product adoption for AI: Own activation, onboarding, and the path to habitual use. Reduce friction, design for time to value, and grow adoption across new customers, existing customers, and internal teams. 
  • Drive growth: Build and instrument growth loops, expansion, and retention. Partner with go-to-market and growth to turn capability into usage, usage into value, and value into revenue. 
  • Decide with data: Instrument every experience, define the metrics that matter, and run a disciplined experimentation practice (A/B tests, funnels, cohort analysis) so decisions are grounded in evidence, not opinion. 
  • Run continuous discovery: Engage customers and prospects through interviews, onsite visits, workshops, and discovery sessions. Map opportunities to solutions, validate before building, and keep a living view of unmet needs. 
  • Master the market: Develop deep expertise in DFIR, the agentic AI landscape, competitive dynamics, and emerging model and tooling trends to inform strategic bets. 
  • Navigate competing priorities: Make thoughtful tradeoffs across scope, quality, trust, and timelines while staying aligned to strategic objectives. 
  • Drive clarity: Break ambiguous problem spaces into structured, actionable plans that align leadership and let teams execute with confidence. 
  • Lead strategic visibility and alignment: Track the metrics that signal success and give clear, outcome-focused updates to executives and cross-functional partners. 
  • Collaborate across teams: Partner with engineering, UX, data science, and peer PMs to deliver experiences that are intuitive, consistent, and aligned to key personas. 
  • Influence cross-functionally: Build strong relationships with GTM, customer success, support, and leadership to drive alignment and optimize results. 
  • Work AI-natively: Default to AI across your own workflow (discovery, research, analysis, drafting, and prototyping) and model AI-native ways of working that raise the bar for the wider product team. 
  • Travel: 5-15%. 
What We're Looking For

  • Agentic AI experience (required): You have built and shipped agentic or AI-native product experiences (agents, copilots, autonomous or semi-autonomous workflows) in production. You can speak concretely to what you shipped, what worked, and what did not. 

  • AI-native operator (required): You use AI as a default part of how you work, not an occasional assist. You are fluent with current AI tools and prompt engineering for research, discovery synthesis, competitive analysis, drafting (PRDs, specs, user stories), data analysis, and rapid prototyping. 

  • Experience: 7-10 years in product management, ideally with enterprise SaaS, including meaningful time on AI or ML-powered products. 

  • Adoption and growth: Demonstrated track record driving product adoption, activation, retention, and growth, ideally in a product-led motion. 

  • Data-driven decision making: Fluent with product analytics and experimentation. You instrument what you build and let metrics guide tradeoffs. 

  • Product discovery: Skilled in continuous discovery and validation techniques (customer interviews, opportunity-solution mapping, Jobs To Be Done). 

  • Technical acumen: Able to partner closely with engineering and data science on AI system design (models, retrieval, evaluation, latency, cost) and to reason about tradeoffs across complexity, scalability, trust, and customer value. 

  • Analytical mindset: Skilled at interpreting market data, customer insight, and usage metrics to drive decisions. 

  • Influence and communication: Strong collaboration skills and the ability to communicate effectively with both technical teams and executive stakeholders. 

  • Ownership mindset: Act as the champion for your product, anticipating challenges, removing obstacles, and driving momentum to meaningful business results. 

Nice to Have Skills

  • Industry experience in Digital Forensics, Incident Response, cybersecurity, or other regulated, high-trust domains. 

  • Hands-on experience with modern AI tooling and patterns (LLM orchestration, RAG, agent frameworks, evaluations, guardrails). 

  • Familiarity with AI governance, safety, or responsible AI practices in a product context. 

  • Experience building within On-Premise and Hybrid Deployment models. 

  • Experience with Pragmatic Marketing, Design Thinking, Jobs To Be Done, or Continuous Discovery, or equivalent. 

  • Comfort building working prototypes or demos with AI app builders and coding copilots. 

  • Experience in Agile development and familiarity with product and analytics tooling including Jira, Aha, and Amplitude. 

Compensation & Benefits 

The Compensation range is for the primary location for which the job is posted. Please note that the actual compensation may vary depending on location and job-related factors such as qualifications, experience, knowledge and skills. If you are applying for this role outside of the primary location and you are selected for an interview, the Talent Acquisition Partner can share more information with you.If the compensation structure for the role includes an incentive component (i.e. most Sales roles) the range below represents total target compensation (TTC) (base salary + variable).  
 

$175,000 - $225,000 (CDN) a year  
$150,000 - $200,000 (USD) a year
Salary range (min - max) 
 

Position Type: New Position


Magnet is proud to offer benefits such as: 
 
- Generous time off policies 
- Competitive compensation 
- Volunteer opportunities  
- Reward and recognition programs   
- Employee committees & resource groups  
- Healthcare and retirement benefits 
 
Indicators of Success
 
We're looking for someone who checks off most, but not all, of the boxes listed in "skills and experiences".  It's more important to us to find candidates who can display indicators of success through skills they have developed and experiences they have been a part of, than to find folks who have "been there, done that".  We want to be part of your development journey, and we'll learn as much from you as you learn from us. 
 
How We Work
 
At Magnet Forensics, we take a hybrid-flexible approach to support your productivity and work-life balance. If you're within a comfortable travel distance to one of our offices, you'll occasionally join us in person. How often you'll come in depends on your department and team needs, typically ranging from weekly to monthly. These in-person moments help us build stronger connections, spark new ideas, and celebrate our successes together. Most days, you can choose what works best for you, while staying in tune with your team's goals.
 
We're excited to welcome you to our team and look forward to achieving great things together - both in the office and wherever you work best!
 
The Most Important Thing
 
We're looking for candidates that can provide examples of how they have demonstrated Magnet CODE in their previous experiences:
 
CARE - We care about each other and our mission to make a difference in the world.
OWN - We are accountable for our results - while never forgetting to act with integrity, empathy, and respect.
DEDICATE - We put our heart and soul into meeting the needs of our customers and helping them serve the people they protect.
EVOLVE - We are constantly innovating and exploring new ways to work together to make an impact with our work.
 
Here at Magnet Forensics, we are committed to continuous learning and are focused on building a diverse and inclusive workforce. This commitment will be reflected in our hiring processes and embedded in our values and how we treat one another. If you're interested in this role, but do not meet all of the qualifications listed above, we encourage you to apply anyways.
 
Magnet Forensics is an Equal Opportunity Employer and considers applicants for employment without regard to race, colour, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, provincial, or local law. We are committed to providing an inclusive, accessible recruitment process and work environment...

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