1 month ago
Chennai, IndiaStaff+
Responsibilities
- Design scalable end-to-end generative AI architectures, solution blueprints, and reference architectures for complex enterprise problems.
- Integrate generative AI models with existing systems and data pipelines to deliver reliable, reusable capabilities.
- Architect AWS cloud-native solutions and establish CloudFormation-based infrastructure automation and governance.
- Define and optimize machine learning workflows for data preparation, training, tuning, deployment, monitoring, scaling, storage, and compute utilization.
- Translate business requirements into technical designs and advise stakeholders on architectural options, tradeoffs, and recommendations.
- Guide secure AI design practices covering data protection, access control, observability, compliance, and responsible AI.
- Review solution designs and implementation plans, identify risks and gaps, and ensure adherence to architectural standards.
- Coordinate with platform and operations teams on high availability, resilience, and disaster recovery for AWS AI workloads.
- Document architectural decisions, patterns, and guidelines and mentor teams on AI and cloud architecture.
Requirements
- Extensive hands-on experience designing and implementing production generative AI solutions, including model integration, prompt engineering, and lifecycle management.
- Strong proficiency with AWS CloudFormation, including authoring modular templates, managing stacks, and enforcing infrastructure automation practices.
- Proven expertise with AWS machine learning services such as SageMaker across data preparation, training, deployment, and model monitoring.
- Background in distributed systems, microservices, and event-driven architectures.
- Experience collaborating with distributed teams in hybrid work environments using remote-friendly communication and delivery practices.
- Preferred experience with MLOps tools and frameworks for machine learning and generative AI workflows.
- Preferred experience with data governance, data quality, and metadata management for training and inference data.
- Preferred experience mentoring technical teams and contributing to architecture-focused communities of practice.
- Industry knowledge in finance, retail, or healthcare is preferred.
- Awareness of ethical AI guidelines and regulatory considerations is preferred.
Benefits
- Hybrid work model.
Tech Stack
Categories
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.