Sr. Solutions Architect AI

What You’ll Do

• Lead Technical Strategy & Design: Architect and oversee the implementation of enterprise-scale AI/ML and GenAI platforms across AWS, Azure, GCP, and Databricks.
• Be the Client-Facing Expert: Lead discovery workshops to surface high-impact use cases, translate complex business requirements into architectural roadmaps, and present ROI models to executive stakeholders.
• Architect the Future: Design reference architectures on Databricks covering data pipelines, feature stores, model training, vector databases, and real-time inference.
• Own the Ecosystem: Drive strategic relationships with AWS, Azure, GCP, and Databricks, ensuring our offerings leverage the latest innovations in GenAI and MLOps.
• Set the Standard: Define best practices for responsible AI, data quality, and security, serving as the final point of escalation for complex technical challenges.
• Mentor and Multiply: Lead and grow a multidisciplinary team of engineers and data scientists, acting as a "force multiplier" through technical guidance and design reviews.
• Market Leadership: Represent Megazone Cloud at industry conferences, publish white papers, and position the firm as a premier leader in applied-AI innovation.

What You Bring (Requirements)

• Professional Experience: 8-12+ years of experience in data science, AI, and data ecosystems, with at least 5 years leading cross-functional technical teams.
• Databricks Mastery: Deep, hands-on expertise with the Databricks stack and a proven track record of integrating Databricks into complex client environments.
• Cloud Architecture: 2+ years of progressive experience in cloud architecture or solutions engineering across AWS, Azure, or GCP.
• Strategic Leadership: Proven ability to build, manage, and mentor technical teams while managing multi-faceted projects.
• C-Suite Excellence: Exceptional skills in presenting to executive audiences and translating business needs into technical designs.
• Educational Foundation: Bachelor’s degree in Computer Science, Data Science, or a related field (Master’s or PhD preferred).
• A "Builder" Mindset: A startup mentality, a strategic approach to problem-solving, and a genuine thirst for knowledge.

Bonus Points (Nice-to-Haves)

• Relevant high-level certifications (e.g., Databricks Machine Learning Professional, AWS ML Specialty, Azure AI Engineer, or Google Professional ML Engineer).
• Experience in a Professional Services or consulting environment.