Cognizant is hiring an Enterprise Architect to architect and implement the AI Training Data Service (AITDS) platform. This is a hands-on technical role where you will define end-to-end architecture, select cloud-native services, and guide implementation to create a scalable, secure, and optimized foundation for enterprise AI readiness.
What You'll Do
- Define the AITDS platform architecture, covering data ingestion, profiling, annotation, validation, governance, and deployment workflows.
- Design modular, API-driven components for seamless integration with enterprise systems and cloud ecosystems.
- Select and integrate services across AWS (S3, Glue, SageMaker, Redshift), Azure (Data Factory, Synapse, Cognitive Services), and GCP (BigQuery, Vertex AI, Dataflow).
- Optimize architecture for cost, performance, and scalability across multiple cloud providers.
- Work closely with engineering teams to implement architecture using containerization (Docker/Kubernetes), microservices, and serverless technologies.
- Define CI/CD pipelines and DevOps practices for platform deployment.
- Architect solutions for high-quality training data generation, annotation, and validation for AI/ML models.
- Ensure compliance with data governance, privacy, and ethical AI standards.
- Identify new tools, products, and partners to accelerate platform development.
- Make informed build vs. buy decisions for data and AI components.
- Introduce advanced techniques like synthetic data generation, automated annotation, and AI-driven data quality checks.
What We're Looking For
- Proven experience in designing large-scale, cloud-native platforms.
- Hands-on experience with AWS, Azure, and GCP services and products.
- Strong background in data pipelines, ETL, and big data technologies like Spark and Hadoop.
- Deep understanding of the AI/ML lifecycle and data preparation for model training.
- Expertise in containerization (Docker/Kubernetes), microservices, and API-driven design.
- Experience with CI/CD pipelines and Infrastructure as Code tools like Terraform and CloudFormation.
- Ability to assess third-party tools and make strategic build vs. buy decisions.
- Ability to guide technical teams and ensure architectural integrity throughout implementation.
Nice to Have
- Experience with AI data platforms, MLOps, and data labeling tools.
- TOGAF or similar enterprise architecture certification.
- Advanced degree in Computer Science, Data Science, or a related field.
Technical Stack
- Clouds: AWS, Azure, GCP
- AWS Services: S3, Glue, SageMaker, Redshift
- Azure Services: Data Factory, Synapse, Cognitive Services
- GCP Services: BigQuery, Vertex AI, Dataflow
- Infrastructure: Docker, Kubernetes, Terraform, CloudFormation
- Data Processing: Spark, Hadoop
Work Mode
This position follows a local-country work mode and is open to candidates across PAN India.
