Job Title: Senior AI Architect
Location: Onsite (4 Days/Week)
8–10+ years of experience in Software Engineering or Data Architecture.
Minimum 4+ years of hands-on experience designing and deploying AI/ML systems in production environments.
Required Qualifications
Enterprise AI Strategy
Lead the transition of AI initiatives from Proof of Concepts (PoCs) to scalable, enterprise-wide production systems.
AI Technology Selection
Evaluate and recommend AI technologies, including Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI, based on business requirements, cost, latency, and data privacy considerations.
AI Architecture
Design end-to-end AI solutions, including data ingestion, model training/fine-tuning, deployment, monitoring, and lifecycle management.
MLOps & Infrastructure
Design and implement MLOps practices for Continuous Integration (CI), Continuous Deployment (CD), and Continuous Training (CT) to ensure model reliability and prevent model drift.
Data & Integration
Collaborate with Data Engineering teams to design scalable AI data architectures, including Vector Databases, Retrieval-Augmented Generation (RAG) workflows, and enterprise data pipelines.
AI Governance & Security
Establish AI governance frameworks to ensure fairness, transparency, security, and compliance with data privacy regulations such as GDPR and CCPA.
Cost Management
Optimize AI infrastructure costs, including GPU utilization, token optimization, and efficient resource management for large AI workloads.
Communication & Leadership
Effectively communicate AI strategies, capabilities, and limitations to executive leadership and non-technical stakeholders.
Provide technical leadership across cross-functional teams.
Technical Skills
Generative AI
Machine Learning & Deep Learning
Natural Language Processing (NLP)
Computer Vision
Python
MLOps
CI/CD
Vector Databases
RAG Architecture
SQL
Snowflake / BigQuery
AI Infrastructure & Cloud Platforms
