AI Data Architect

Ryan Specialty•Carmel, IN

1d•$160,000 - $200,000

About The Position

Position Summary The AI Architect designs and implements artificial intelligence infrastructure. Bridge the gap between complex AI models and systems and business applications. Partner with key business and technology stakeholders to create blueprints for AI systems, choose technologies and ensure secure, scalable, and compliant production deployment. Key responsibilities include overseeing data pipelines, managing model lifecycles, and collaborating with engineers. What will your job entail? Key Responsibilities Architectural Design: Create end-to-end AI system blueprints, encompassing data ingestion, processing, model training, and deployment. Technology Strategy and Selection: Evaluate and choose AI frameworks, platforms, and tools that meet business requirements, partnering with key technology and business stakeholders. Deployment and Lifecycle Management: Oversee the transition from POC (Proof of Concept) to production, ensuring continuous model monitoring, retraining, and stability. Data Strategy: Define strategies for collecting, cleaning, and managing high-quality datasets for training. Security and Compliance: Embed AI ethics, data privacy, and security controls within the architecture. Stakeholder Collaboration: Translate complex AI concepts into actionable business strategies for non-technical stakeholders.

Requirements

Technical Expertise: Deep knowledge of AI/ML algorithms, neural networks, Natural Language Processing (NLP), and data engineering.
Experience: Previous experience as an AI Engineer, Data Scientist, or technical leader is highly valued.
Cloud Proficiency: Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
Programming Skills: Proficiency in Python and familiarity with data manipulation tools.
Education: Ideally a degree in Computer Science, Data Science, or AI.
Soft Skills: Strong leadership, communication, and strategic thinking capabilities.

Responsibilities

Architectural Design: Create end-to-end AI system blueprints, encompassing data ingestion, processing, model training, and deployment.
Technology Strategy and Selection: Evaluate and choose AI frameworks, platforms, and tools that meet business requirements, partnering with key technology and business stakeholders.
Deployment and Lifecycle Management: Oversee the transition from POC (Proof of Concept) to production, ensuring continuous model monitoring, retraining, and stability.
Data Strategy: Define strategies for collecting, cleaning, and managing high-quality datasets for training.
Security and Compliance: Embed AI ethics, data privacy, and security controls within the architecture.
Stakeholder Collaboration: Translate complex AI concepts into actionable business strategies for non-technical stakeholders.
Exposing AI/ML models into APIs.
Designing and prototyping AI system.
Reviewing AI systems to ensure scale and compliance with company policy and regulations.
Mentoring teams of data scientists and AI engineers.