Senior AI Solution Architect – Azure, Databricks & Agentic AI

Cognizant; Washington (District of Columbia); On-site; USD 157,000 - 180,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays & PTO

401(k) plan

Disability insurance

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant in the United States (Washington, DC area) seeks a Senior AI Solution Architect to lead design and deployment of enterprise AI, Generative AI, and agentic AI solutions using Azure, Databricks, Fabric, and LLMs. You will translate business goals into secure, production-ready AI systems and guide cross-functional teams.

The role requires 10+ years in solution/enterprise architecture and 5+ years delivering AI projects, with deep Azure expertise and leadership of architecture reviews and

Qualifications

• 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 and related cloud services.
• Strong experience with Azure Databricks, Delta Lake, Lakehouse architecture, Microsoft Fabric, 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.

Responsibilities

• Define enterprise AI strategy, reference architectures, reusable design patterns, and governance standards aligned with business and technology objectives.
• 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 using LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, and MCP.
• Establish orchestration patterns for tool calling, memory management, context engineering, autonomous workflows, multi-agent coordination, and human-in-the-loop controls.
• Design modern data platforms using Azure Databricks, Delta Lake, Microsoft Fabric, Azure Data Lake Storage, and Azure Synapse Analytics.
• Architect batch and real-time data pipelines, data products, metadata, lineage, data quality, master data management, and self-service analytics capabilities.
• Design secure, scalable, and 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.

Skills

AI architecture

Generative AI

LLMs

Multi-agent systems

Azure cloud

Data engineering

Leadership

Security & compliance

Tools

Azure Databricks

Delta Lake

Microsoft Fabric

Azure Data Lake Storage

Azure Synapse Analytics

AKS

Azure Functions

API Management

Cosmos DB

Azure AI Search

Event Hubs

Service Bus

Job description

Practice - AIA - Artificial Intelligence and Analytics
About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.
By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery models. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.
Job Summary
We are seeking a Senior AI Solution Architect to lead the design and implementation of enterprise-scale AI, Generative AI, and agentic AI solutions. This role will define scalable AI architectures leveraging Microsoft Azure, Azure Databricks, Microsoft Fabric, Large Language Models, RAG, and multi-agent frameworks. The ideal candidate will combine hands-on AI engineering expertise with enterprise architecture, data platform, integration, security, and responsible AI capabilities. This position requires a strategic technology leader who can translate business goals into secure, production-ready AI solutions and guide cross-functional teams through enterprise AI adoption.
In This Role, You Will

• Define enterprise AI strategy, reference architectures, reusable design patterns, and governance standards aligned with business and technology objectives.
• 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 using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, and Model Context Protocol (MCP).
• Establish orchestration patterns for tool calling, memory management, context engineering, autonomous workflows, multi-agent coordination, and human-in-the-loop controls.
• Design modern data platforms using Azure Databricks, Delta Lake, Microsoft Fabric, Azure Data Lake Storage, and Azure Synapse Analytics.
• Architect batch and real-time data pipelines, data products, metadata, lineage, data quality, master data management, and self-service analytics capabilities.
• Design secure, scalable, and 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.
  

What You Need To Have To Be Considered

• 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, Azure AI Search, and related cloud services.
• 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.
  

#CB
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Applications will be accepted until 30 Oct 2026.
Salary And Other Compensation
The annual salary for this position is between $[156,500 -180,000] depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan