Intellectt Inc
Enterprise Architect (AI/ML) (Atlanta)
Intellectt Inc, Atlanta, Georgia, United States, 30383
Role:
Enterprise Architect (AI/ML) Location : Atlanta, GA--Onsite Duration : Full Time
Key Responsibilities: Define and execute the companys enterprise technology roadmap aligned with business objectives and AI-first strategy. Lead the architecture, design, and implementation of scalable, secure, and cloud-native systems. Drive AI/ML and Generative AI initiatives, leveraging LLMs, OpenAI/GenAI platforms, and emerging technologies to enhance products and operations. Architect and oversee solutions leveraging AWS, Azure, or GCP, ensuring high availability and performance. Establish enterprise architecture standards, governance, and best practices across teams. Collaborate with product, data, and business leadership to define technical strategy and priorities. Guide teams on data platforms, MLOps, AI governance, and model lifecycle management. Ensure security, compliance, and data governance across cloud and AI systems. Evaluate and adopt new tools, frameworks, and platforms to drive innovation and operational efficiency. Mentor and lead architecture, engineering, and data science teams. Required Skills & Qualifications: 10+ years of progressive experience in software engineering, architecture, and technology leadership. Strong hands-on experience with AI/ML and Generative AI (LLMs, prompt engineering, model deployment). Proven expertise in cloud platforms: AWS, Azure, or GCP. Solid understanding of enterprise, cloud-native, and data-driven architectures. Experience with Python, Java, and modern backend frameworks. Knowledge of data platforms, APIs, microservices, and event-driven systems. Strong understanding of security, scalability, and performance optimization. Proven ability to influence stakeholders and lead cross-functional teams. Bachelors or Masters degree in Computer Science, Engineering, or related field. Preferred Qualifications: Experience with MLOps, CI/CD, DevOps, Docker, and Kubernetes. Exposure to AI governance, responsible AI, and compliance frameworks. Familiarity with big data, analytics, and real-time data processing. TOGAF or similar enterprise architecture certification is a plus. Experience working in startup or large-scale enterprise environments.
Enterprise Architect (AI/ML) Location : Atlanta, GA--Onsite Duration : Full Time
Key Responsibilities: Define and execute the companys enterprise technology roadmap aligned with business objectives and AI-first strategy. Lead the architecture, design, and implementation of scalable, secure, and cloud-native systems. Drive AI/ML and Generative AI initiatives, leveraging LLMs, OpenAI/GenAI platforms, and emerging technologies to enhance products and operations. Architect and oversee solutions leveraging AWS, Azure, or GCP, ensuring high availability and performance. Establish enterprise architecture standards, governance, and best practices across teams. Collaborate with product, data, and business leadership to define technical strategy and priorities. Guide teams on data platforms, MLOps, AI governance, and model lifecycle management. Ensure security, compliance, and data governance across cloud and AI systems. Evaluate and adopt new tools, frameworks, and platforms to drive innovation and operational efficiency. Mentor and lead architecture, engineering, and data science teams. Required Skills & Qualifications: 10+ years of progressive experience in software engineering, architecture, and technology leadership. Strong hands-on experience with AI/ML and Generative AI (LLMs, prompt engineering, model deployment). Proven expertise in cloud platforms: AWS, Azure, or GCP. Solid understanding of enterprise, cloud-native, and data-driven architectures. Experience with Python, Java, and modern backend frameworks. Knowledge of data platforms, APIs, microservices, and event-driven systems. Strong understanding of security, scalability, and performance optimization. Proven ability to influence stakeholders and lead cross-functional teams. Bachelors or Masters degree in Computer Science, Engineering, or related field. Preferred Qualifications: Experience with MLOps, CI/CD, DevOps, Docker, and Kubernetes. Exposure to AI governance, responsible AI, and compliance frameworks. Familiarity with big data, analytics, and real-time data processing. TOGAF or similar enterprise architecture certification is a plus. Experience working in startup or large-scale enterprise environments.