- 7to 15 years of overall IT experience.
- Minimum 3+ years in Enterprise Architecture, AI Architecture, or Digital Transformation leadership roles.
- Proven experience designing and deploying enterprise-scale AI and Generative AI solutions.
- Experience leading large-scale technology transformation programs across multiple business domains.
- Strong experience working directly with executive stakeholders and client architecture boards.
- Agentic AI
- Generative AI
- AI Functional Architecture
- Enterprise Architecture
- Responsible AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Multi-Agent Systems
- AI Governance & Compliance
- Cloud-native AI Architectures
- AI Platform Strategy
- Enterprise Digital Transformation
- AI Strategy & Governance
- Regulated Business Processes
- Human-in-the-Loop AI Systems
- Financial Services
- Healthcare & Life Sciences
- Insurance
- Regulatory Technology
- Cloud Platforms (Azure, AWS, GCP)
- AI Security & Risk Management
- MLOps and AI Operations
- Design AI-native enterprise architectures for large transformation programs.
- Define human-agent capability matrices and operating models for AI-enabled delivery.
- Architect multi-agent ecosystems that integrate enterprise applications, data platforms, and business processes.
- Develop scalable context engineering and knowledge orchestration frameworks.
- Define guardrails, policies, and boundary specifications for agentic AI systems.
- Establish governance models for AI autonomy, decision-making, and escalation controls.
- Design human oversight mechanisms for enterprise AI operations.
- Create standards for AI system traceability, transparency, and auditability.
- Architect Responsible AI frameworks covering:
- Bias detection and mitigation
- Explainability
- Model transparency
- Ethical AI adoption
- Audit trail design
- Ensure compliance with corporate, industry, and regulatory AI requirements.
- Lead client architecture workshops and executive design reviews.
- Govern AI-First Application Development Lifecycle (ADLC) adoption across delivery portfolios.
- Define standards for AI-generated code quality, validation, and production readiness.
- Drive reusable AI architecture patterns, accelerators, and playbooks across engagements.
- Design AI-powered decisioning systems for regulated industries.
- Define compliance controls and governance checkpoints for high-risk AI use cases.
- Establish monitoring and observability frameworks for AI-driven business processes.
- Act as a trusted advisor to clients and internal leadership teams.
- Influence AI strategy, architecture standards, and innovation roadmaps.
- Mentor architects, AI engineers, and enterprise technology leaders.
- Contribute to Cognizant's AI intellectual property, frameworks, and industry best practices.
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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