Job Description: Sr. Enterprise Architect
Location: PAN India
Level: Director
Experience Level: 20+ years in Data, AI, and Platform Engineering
Job Title: Enterprise Architect – AI Training Data Services
Role Overview
We are looking for a hands-on Enterprise Architect with strong technical expertise in data platforms, AI/ML lifecycle, and multi-cloud architecture (AWS, Azure, GCP). This role will define and implement the end-to-end architecture and design for Cognizant’s AI Training Data Service (AITDS) platform, ensuring it is scalable, secure, and optimized for enterprise AI readiness.
This position requires deep technical involvement—from designing architecture blueprints to selecting cloud-native services, partnering with external products and guiding implementation.
Key Responsibilities
- Architecture Design & Implementation
- Define the AITDS platform architecture, including data ingestion, profiling, annotation, validation, governance, and deployment workflows.
- Design modular, API-driven components for integration with enterprise systems and cloud ecosystems.
- Multi-Cloud Expertise
- Select and integrate services from 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.
- Hands-on Technical Leadership
- 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.
- Data & AI Readiness
- 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.
- Product & Partner Evaluation
- Identify new tools, products, and partners to accelerate platform development.
- Make informed build vs. buy decisions for data and AI components.
- Innovation
- Introduce advanced techniques like synthetic data generation, automated annotation, and AI-driven data quality checks.
Required Skills & Experience
- Enterprise Architecture: Proven experience in designing large-scale, cloud-native platforms.
- Multi-Cloud Expertise: Hands-on experience with AWS, Azure, and GCP services and products.
- Data Engineering: Strong background in data pipelines, ETL, big data technologies (Spark, Hadoop).
- AI/ML Knowledge: Deep understanding of AI/ML lifecycle and data preparation for model training.
- Platform Engineering: Expertise in containerization (Docker/Kubernetes), microservices, and API-driven design.
- DevOps & Automation: Experience with CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation).
- Strategic Product Evaluation: Ability to assess third-party tools and make build vs. buy decisions.
- Leadership: Ability to guide technical teams and ensure architectural integrity.
Preferred Qualifications
- Experience with AI data platforms, MLOps, and data labeling tools.
- TOGAF or similar enterprise architecture certification.
- Advanced degree in Computer Science, Data Science, or related field.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
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