AI Architect
On-siteBengaluru, Karnataka, India
Job Summary
Develop and maintain the enterprise AI roadmap aligned with business objectives while evaluating new technologies and vendors. Design scalable, secure, cloud-native AI/ML architectures and define MLOps frameworks for continuous training, deployment, and monitoring. Lead AI/ML initiatives across multiple business units, working with data scientists and software teams to deliver production-grade models and optimize workloads for cost and performance. Translate business challenges into AI use cases with measurable outcomes and present technical recommendations to executive leadership. Establish governance frameworks for responsible AI, privacy, and ethics, ensuring compliance with data protection laws and implementing controls to prevent bias and model drift.
Required Qualifications
- 12–15+ years of overall experience
- 4+ years in AI/ML architecture or leadership roles
- Strong understanding of Machine learning
- Strong understanding of deep learning
- Strong understanding of NLP
- Strong understanding of LLMs
- Strong understanding of RAG
- Strong understanding of transformers
- Experience with Azure AI
- Experience with AWS Sagemaker
- Experience with Google Vertex AI
- Experience with MLflow
- Experience with Databricks
- Experience with Kubeflow
- Experience with Airflow
- Experience with Docker
- Experience with Kubernetes
- Experience with Spark
- Experience with Data Factory
- Experience with pipelines
- Experience with ETL/ELT
- Programming in Python
- Programming in SQL
- Familiarity with TensorFlow
- Familiarity with PyTorch
- Experience designing enterprise-grade AI systems
- Experience designing microservices architectures
- Strong communication skills
- Stakeholder-management skills
- Ability to balance technical depth with strategic thinking
- Leadership experience with cross-functional teams
Desired Qualifications
- Master's degree in Computer Science, AI, Data Science, or related fields
- Bachelor's degree in Computer Science, AI, Data Science, or related fields
- Certifications in cloud (Azure AI Engineer, AWS ML Specialty, etc.)
- Experience implementing generative AI and LLM solutions in production
- Background in industry-specific domains (finance, telecom, retail, healthcare, etc.)
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