5 days ago
Base Salary
$157k - $180k/yr
Responsibilities
- Define enterprise AI strategies, reference architectures, reusable design patterns, and governance standards.
- Architect Generative AI and agentic AI solutions using Azure AI Foundry, Azure OpenAI, Azure AI Agent Service, LLMs, RAG, knowledge graphs, and vector databases.
- Design multi-agent systems and orchestration patterns for tool calling, memory management, context engineering, autonomous workflows, coordination, and human-in-the-loop controls.
- Design modern data platforms and batch or real-time data pipelines using Azure Databricks, Delta Lake, Microsoft Fabric, Azure Data Lake Storage, and Azure Synapse Analytics.
- Architect secure, scalable, resilient cloud-native solutions using AKS, Azure Functions, API Management, Cosmos DB, Azure AI Search, Event Hubs, Service Bus, and Azure SQL.
- Establish Responsible AI, model governance, evaluation, observability, explainability, security, privacy, and AI risk-management frameworks.
- Lead architecture review boards, technical workshops, solution assessments, proofs of concept, modernization programs, and executive stakeholder discussions.
- Mentor architects, engineers, data scientists, and product teams while driving reusable AI platform capabilities and engineering best practices.
Requirements
- 10+ years of experience in Solution Architecture, Enterprise Architecture, Cloud Architecture, Data Engineering, or Software Engineering.
- 5+ years of hands-on experience delivering AI, Machine Learning, Data Science, or advanced analytics solutions.
- 3+ years of experience implementing enterprise Generative AI, RAG, LLM, or agentic AI solutions.
- Deep expertise in Microsoft Azure, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning, AKS, API Management, and Azure AI Search.
- Strong experience with Azure Databricks, Delta Lake, Lakehouse architecture, Microsoft Fabric, Azure Data Lake Storage, and modern data engineering patterns.
- Hands-on knowledge of LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, MCP, or comparable AI orchestration frameworks.
- Strong understanding of LLMs, embeddings, vector databases, RAG, knowledge graphs, AI agents, tool calling, memory, and multi-agent coordination.
- Experience designing API-first, event-driven, microservices, and cloud-native integration architectures for enterprise AI platforms.
- Strong knowledge of AI security, Zero Trust, identity management, data privacy, model governance, Responsible AI, and regulatory compliance.
- Proven experience leading cross-functional teams, architecture governance processes, and executive-level technology discussions.
Benefits
- Medical, dental, vision, and life insurance, subject to applicable eligibility requirements.
- Paid holidays and paid time off.
- 401(k) plan and contributions.
- Long-term and short-term disability coverage.
- Paid parental leave.
- Employee Stock Purchase Plan.
- Eligible for Cognizant’s discretionary annual incentive program based on performance and applicable plan terms.
Tech Stack
AzureDatabricks
Categories
Solutions Engineering
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.