Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...
Integration Architect
Atlanta, GA · On-site
$68 - $87.75/hr
... with explainable AI (XAI) techniques. • Experience with MLOps and model deployment pipelines. • Experience with containerization technologies (e.g., Docker, Kubernetes). • Experience with ...
Integration Architect
Atlanta, GA · On-site
$68 - $87.75/hr
... with explainable AI (XAI) techniques. • Experience with MLOps and model deployment pipelines. • Experience with containerization technologies (e.g., Docker, Kubernetes). • Experience with ...
Sr. Manager, Client Engagement AI Enablement and Transformation
Alpharetta, GA · On-site
$115 - $192/hr
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows.* Ensure solutions align with responsible AI principles ...
Sr. Manager, Client Engagement AI Enablement and Transformation
Alpharetta, GA · On-site
$115 - $192/hr
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows.* Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Partner across Client Engagement, Product, Technology, and other functions to embed usable, explainable AI capabilities into daily workflows. * Ensure solutions align with responsible AI principles ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Product Manager - Technology
Atlanta, GA · On-site
What Success Looks Like Human-Centered AI Design - Builds intuitive, trustworthy, and explainable AI systems that solve real user pain points, drive adoption, and reduce friction across technical and ...
Senior Agentic (AI) Engineer
Atlanta, GA · On-site +1
$100K - $138K/yr
Experience designing explainable / auditable AI workflows for regulated environments. * Open-source contributions to agent frameworks, eval tooling, or retrieval libraries. * AWS depth (EKS, MSK, RDS ...
Senior Agentic (AI) Engineer
Atlanta, GA · On-site +1
$100K - $138K/yr
Experience designing explainable / auditable AI workflows for regulated environments. * Open-source contributions to agent frameworks, eval tooling, or retrieval libraries. * AWS depth (EKS, MSK, RDS ...
... and Explainable AI. • Use programming languages like Python, Scala, or Java. • API development Required Skills: • At least 4 years of experience programming with Python, Scala, or Java ...
... and Explainable AI. • Use programming languages like Python, Scala, or Java. • API development Required Skills: • At least 4 years of experience programming with Python, Scala, or Java ...
... and Explainable AI. • Use programming languages like Python, Scala, or Java. • API development Required Skills: • At least 3 years of experience programming with Python, Scala, or Java ...
... and Explainable AI. • Use programming languages like Python, Scala, or Java. • API development Required Skills: • At least 3 years of experience programming with Python, Scala, or Java ...
Snowflake Architect
Alpharetta, GA · On-site
$62.25 - $80/hr
Ensure AI outputs are explainable, auditable and repeatable. Partner with Data Platform Architects to ensure semantic views and certified datasets are AI ready. Advice on shaping medallion layers and ...
Snowflake Architect
Alpharetta, GA · On-site
$62.25 - $80/hr
Ensure AI outputs are explainable, auditable and repeatable. Partner with Data Platform Architects to ensure semantic views and certified datasets are AI ready. Advice on shaping medallion layers and ...
A deep commitment to developing AI that is explainable, fair, and safe for the world's largest workforces. Workday Pay Transparency Statement The annualized base salary ranges for the primary ...
A deep commitment to developing AI that is explainable, fair, and safe for the world's largest workforces. Workday Pay Transparency Statement The annualized base salary ranges for the primary ...
Consultant AI & Data Engineer
Atlanta, GA · On-site
Translate operational processes into structured and/or agentic AI workflows, designing human-in-the-loop and explainable escalation patterns for sensitive tasks where AI/automation alone is ...
Consultant AI & Data Engineer
Atlanta, GA · On-site
Translate operational processes into structured and/or agentic AI workflows, designing human-in-the-loop and explainable escalation patterns for sensitive tasks where AI/automation alone is ...
Explainable Ai information
What is Explainable AI?
What are the key skills and qualifications needed to thrive as an Explainable AI specialist?
What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?
What is the difference between Explainable Ai vs Data Scientist?
| Aspect | Explainable Ai | Data Scientist |
|---|---|---|
| Credentials | Typically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are common | Requires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial |
| Work Environment | Works within AI development teams, focusing on model transparency and interpretability | Works across data analysis, model building, and business insights, often in research or corporate settings |
| Industry Usage | Used in AI development, healthcare, finance, and any field requiring transparent AI models | Applied 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:

Full-time
Medical, Life, Retirement, PTO
Re-posted 16 days ago
Job description
Role Overview
We are seeking a Data and AI Enterprise Architect with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.
The Enterprise Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.
Enterprise Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.
This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.
The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.
Key Responsibilities
- Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
- Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
- Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
- Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
- Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
- Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
- Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
- Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
- Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
- Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
- Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
- Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
- Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
- Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
- Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
- Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
- Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
- Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
- Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
- Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.
Your Profile
- 4+ years of experience in Enterprise Architecture or Technical Architecture.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
- Strong experience with cloud platforms and services, including:
- Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
- AWS (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
- Databricks
- Handson experience with enterprise data concepts, including:
- Data Intake and Ingestion
- Data Warehousing
- Data Lakes / Lakehouse architectures
- ETL / ELT
- Interactive and operational reporting
- Statistical and regulatory reporting
- Master Data Management (MDM)
- Data Governance, Quality, Security, Audit, Balance & Control
- Solid understanding of enterprise architecture practices, including:
- Architectural patterns
- Roadmaps
- Architecture Review Boards
- Solution Design Boards
- Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
- Experience integrating operational data with enterprise data lakes.
- Strong understanding of data integration challenges and solution patterns.
- Experience with statistical and data science languages such as Python and R (strong asset).
- Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
- Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
- Strong business acumen with deep understanding of:
- Financial systems
- Corporate and backoffice systems
- Enterprise data management, analytics, and AI technology landscape
- Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
- Passion for innovation, continuous improvement, modernization, and change management.
- Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
- High sense of ownership, accountability, and pride in delivered outcomes.
At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.
We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.
The base salary range anticipated for this position is $141,800 - $207,900 plus opportunity for company bonus based upon a percentage of eligible pay. In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).
The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.