Today
Public Trust
Senior Level Career (10+ yrs experience)
No Traveling
IT - Database
Washington, DC (On-Site/Office)
Enterprise Architect – AI/Data
Washington, DC (5 days a week on-site)
Public Trust
You will use your deep knowledge of enterprise architecture principles, AI technologies, and data management practices to guide decision-making and ensure that the architecture supports business objectives and enhances operational capabilities.
Key Responsibilities:
• Design and develop end-to-end AI and data architectures that support business goals, ensuring scalability, performance, security, and maintainability.
• Create architectural blueprints and roadmaps that guide the integration of AI and data solutions across the organization.
• Lead the development and implementation of data platforms and AI-driven systems that facilitate advanced analytics, machine learning, and automation.
• Define AI strategy and guide its implementation across business units, ensuring alignment with business objectives.
• Oversee the deployment and integration of AI models, tools, and technologies into production systems.
• Design and implement scalable cloud-based and on-premises data architectures using platforms like Azure, AWS, or Google Cloud.
• Work with big data technologies (e.g., Hadoop, Spark) and data lake architectures to ensure the organization’s data can be ingested, processed, and analyzed at scale.
• Manage the integration of AI models and algorithms into big data platforms and ensure the appropriate handling of structured and unstructured data.
• Work closely with business and technical teams to understand business needs and translate them into architectural solutions that leverage AI and data analytics.
• Stay current with the latest advancements in AI, machine learning, data technologies, and architecture best practices.
• Lead the adoption and implementation of emerging AI technologies, ensuring the organization remains competitive and innovative.
• Assess and mitigate risks associated with data and AI architectures, ensuring secure handling of sensitive and confidential data.
Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.
• 7+ years of experience in enterprise architecture, with at least 3-5 years of focused experience in AI and data-driven architecture design.
• Extensive experience in enterprise architecture frameworks (e.g., TOGAF, Zachman).
• Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP).
• Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes.
• Hands-on experience with cloud platforms (Azure, AWS, or Google Cloud) for building scalable data solutions.
• Proficiency in data modeling, data warehousing, and ETL processes.
• Familiarity with AI ethics and the implications of machine learning and data use in organizational contexts.
• Strong understanding of how AI and data solutions align with and drive business goals and objectives.
• Ability to address complex architectural and business challenges by designing innovative AI-driven solutions.
• Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Desirable Skills:
• Experience with DevOps practices in AI and data architecture, including continuous integration and deployment (CI/CD) for AI models.
• Familiarity with data privacy regulations (e.g., GDPR, CCPA) and their impact on AI and data architecture.
• Experience with data visualization tools like Power BI, Tableau, or Looker.
• Certifications: Relevant certifications in enterprise architecture, AI, or data science (e.g., TOGAF, Certified Data Management Professional (CDMP), Microsoft Certified: Azure AI Engineer Associate).
Washington, DC (5 days a week on-site)
Public Trust
You will use your deep knowledge of enterprise architecture principles, AI technologies, and data management practices to guide decision-making and ensure that the architecture supports business objectives and enhances operational capabilities.
Key Responsibilities:
• Design and develop end-to-end AI and data architectures that support business goals, ensuring scalability, performance, security, and maintainability.
• Create architectural blueprints and roadmaps that guide the integration of AI and data solutions across the organization.
• Lead the development and implementation of data platforms and AI-driven systems that facilitate advanced analytics, machine learning, and automation.
• Define AI strategy and guide its implementation across business units, ensuring alignment with business objectives.
• Oversee the deployment and integration of AI models, tools, and technologies into production systems.
• Design and implement scalable cloud-based and on-premises data architectures using platforms like Azure, AWS, or Google Cloud.
• Work with big data technologies (e.g., Hadoop, Spark) and data lake architectures to ensure the organization’s data can be ingested, processed, and analyzed at scale.
• Manage the integration of AI models and algorithms into big data platforms and ensure the appropriate handling of structured and unstructured data.
• Work closely with business and technical teams to understand business needs and translate them into architectural solutions that leverage AI and data analytics.
• Stay current with the latest advancements in AI, machine learning, data technologies, and architecture best practices.
• Lead the adoption and implementation of emerging AI technologies, ensuring the organization remains competitive and innovative.
• Assess and mitigate risks associated with data and AI architectures, ensuring secure handling of sensitive and confidential data.
Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.
• 7+ years of experience in enterprise architecture, with at least 3-5 years of focused experience in AI and data-driven architecture design.
• Extensive experience in enterprise architecture frameworks (e.g., TOGAF, Zachman).
• Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP).
• Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes.
• Hands-on experience with cloud platforms (Azure, AWS, or Google Cloud) for building scalable data solutions.
• Proficiency in data modeling, data warehousing, and ETL processes.
• Familiarity with AI ethics and the implications of machine learning and data use in organizational contexts.
• Strong understanding of how AI and data solutions align with and drive business goals and objectives.
• Ability to address complex architectural and business challenges by designing innovative AI-driven solutions.
• Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Desirable Skills:
• Experience with DevOps practices in AI and data architecture, including continuous integration and deployment (CI/CD) for AI models.
• Familiarity with data privacy regulations (e.g., GDPR, CCPA) and their impact on AI and data architecture.
• Experience with data visualization tools like Power BI, Tableau, or Looker.
• Certifications: Relevant certifications in enterprise architecture, AI, or data science (e.g., TOGAF, Certified Data Management Professional (CDMP), Microsoft Certified: Azure AI Engineer Associate).
group id: 10107773
