Description

You will design and lead the transition of AI initiatives from Proof of Concepts to scalable, enterprise-wide production systems.

This role is on-site.

Responsibilities

• Design end-to-end AI architectures covering data ingestion, model training, fine-tuning, deployment, and lifecycle management.
• Evaluate and recommend AI technologies such as Deep Learning, NLP, Computer Vision, and Generative AI based on business requirements, cost, and latency.
• Implement MLOps practices including CI, CD, and CT pipelines to ensure reliable model performance and prevent drift.
• Collaborate with Data Engineering to build scalable data architectures using Vector Databases and RAG workflows.
• Establish AI governance frameworks to ensure fairness, security, and compliance with GDPR and CCPA.

Required Skills

• 8–10+ years of experience in Software Engineering or Data Architecture.
• Minimum 4+ years of hands-on experience designing, developing, and deploying AI/ML systems in production.
• Strong proficiency in Python, Machine Learning, Deep Learning, and NLP.
• Experience with MLOps, CI/CD, and CT pipelines.
• Knowledge of Vector Databases and Retrieval-Augmented Generation (RAG).
• Strong understanding of SQL and modern data warehouses like Snowflake and BigQuery.
• Ability to optimize AI infrastructure costs, including GPU resource allocation.

Preferred Skills

• Experience with Generative AI and Computer Vision.
• Proven leadership in driving enterprise AI initiatives across cross-functional teams.

Key Skills

Education

Bachelor's degree