Technology Architect - Data & AI (6-10 yrs)

Technology Architect (Data and AI).

Job Type : Part-Time (20 Hours/week).

Location : Remote.

Experience Required : 6+ Years of experience in AI data infrastructure.

Hiring Timeline : Immediate 30 Days.

Hiring Process : Resume review Initial screen Technical Interviews (3).

Position Overview :

We are seeking a seasoned Technology Architect Leader specializing in AI Data Infrastructure. This role requires designing, implementing, and optimizing scalable data pipelines, storage solutions, and AI processing frameworks to support advanced AI workloads.

Ideal candidates will have a strong background in building robust data ecosystems for AI applications and hands-on experience in project delivery.

Key Responsibilities :

- Develop and maintain high-level architecture blueprints for AI infrastructure, covering data ingestion, transformation pipelines, scalable storage, and inferencing frameworks.

- Architect and implement data pipelines for structured and unstructured data, leveraging batch (i.e., Matillion, dbt) and streaming solutions (i.e., Kafka, Flink).

- Design and manage scalable data lakes and vector databases to support AI model training and inference.

- Oversee model lifecycle management, including training, evaluation, and MLOps workflows, ensuring continuous optimization and integration of AI models.

- Implement data governance frameworks and compliance measures to safeguard AI data infrastructure.

- Provide hands-on technical leadership while guiding teams in architecting, building, and deploying solutions.

Requirements :

- Proven experience in data architecture with a focus on AI and machine learning infrastructure.

- Proficiency in data engineering tools and frameworks for batch and streaming data.

- Strong understanding of scalable storage solutions and data governance.

- Hands-on experience with AI model lifecycle management and MLOps.

- Excellent problem-solving skills with the ability to lead cross-functional teams.

Preferred Qualifications :

- Certifications in relevant AI, data, or cloud platforms.

- Familiarity with modern data engineering and machine learning tools.

- Experience in driving enterprise-level AI initiatives with measurable impact.