AI Engineer Architect
Designs an enterprise AI platform: evaluates use-case feasibility, picks cloud/on-prem/hybrid deployment models, and integrates AI/ML tooling with data management and analytics while collaborating with data scientists. Core stack: AWS AI/ML services, Python/R/SAS, DevOps (Git, Docker, Kubernetes, CI/CD), and APIs (Apigee, REST/JSON).
- Compensation
- Not disclosed
- Location
- Charlotte, North Carolina, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- 8 years of AI/ML development experience
- Knowledge and implementation experience of AI/ML in AWS Cloud services
- Data science and advanced analytics, including advanced analytics tools such as SAS, R and Python
- DevOps workflows and tools such as Git, containers, Kubernetes and CI/CD
- Bachelor's Degree in a related field (Computer Science, AI/ML)
- AI Architecture - data management, governance, model building and deployment
- APIs, Apigee, Developer Portals; expertise in JSON and RESTful services
- Containers: Docker, Kubernetes, OpenShift, Ansible, Nexus, software defined networking
Full description
AI Engineer Architect needs 8 years AI/ML development experience
AI Engineer Architect requires:
Knowledge and implementation experience of AI/ML in AWS Cloud services;
Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python);
DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
Bachelors Degree in a related field (Computer Science, AI/ML).
Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python).
DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
AI Architecture - data management, governance, model building and deployment
Knowledge and implementation experience of AI/ML in AWS Cloud services
APIs, Apigee, Developer Portals. Expertise in JSON, RESTful services, and similar related tech
Containers: Docker, Kubernetes, OpenShift, Ansible, Nexus, Software defined networking.
AI Engineer Architect duties:
Collaborate with data scientists and other AI professionals
Define the feasibility of use cases along with architectural design for the AI platform
Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools.
Work with Business and delivery partners to understand future requirements and implications for architecture