below marketmost similar roles pay hereabove market
This role pays more than
88%
of similar roles. Most pay
$191,587–$257,212
— the blue band above.
At the midpoint, this role pays about
$288k
versus about
$224k
for comparable roles.
Based on 240 similar postings.
Employer
About Cognizant
Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.
Cognizant currently has
330 open roles
on FindRole.
Listed pay typically runs
$100,000–$135,000
across 211 roles with salary data.
JOB TITLE: Chief Product Architect - Cognitive Intelligence Spine Platform
The Senior Director for the Cognitive Intelligence Spine Platform leads the product, architecture, and client narrative for the flagship sovereign Physical AI platform. This role involves defining the product roadmap, leading pre-sales for C-suite executives, and governing end-to-end technical designs for a unified intelligence fabric. You will manage a globally distributed team of architects and engineers to build scalable systems for industrial sectors like utilities and manufacturing. Key technologies include Microsoft Azure PaaS, specifically Azure AI Foundry, Microsoft Fabric, Cosmos DB, and Azure IoT Hub, alongside NVIDIA embedded environments like Jetson Orin and AGX Orin. You will utilize CUDA, TensorRT, and LangChain to develop agentic AI orchestration, RAG architectures, and sovereign data governance for real-time edge inference and industrial automation.
Define and drive the CIS product roadmap based on market signals and client engagement learnings.
Lead pre-sales and executive engagements with C-suite buyers to present the platform's sovereign AI architecture.
Architect and govern the end-to-end technical design across Azure PaaS, NVIDIA embedded edge, and agentic AI orchestration.
Build and mentor a globally distributed team of senior architects and infrastructure engineers.
Establish engineering standards and architectural review processes to maintain a culture of technical excellence.
Partner with Microsoft and NVIDIA alliance teams to co-develop joint go-to-market capabilities.
Manage client relationships through the full lifecycle from initial architecture workshops to deployment and expansion.
What we're looking for
You must have 15 or more years of experience in enterprise technology.
You must have experience in a senior architecture or product leadership role at a consulting firm, systems integrator, or enterprise software company.
You must have deep, hands-on expertise in Microsoft Azure PaaS, including Azure AI Foundry, Microsoft Fabric, Cosmos DB, Azure IoT Hub, Azure API Management, Azure OpenAI Service, and AKS.
You must have direct experience with NVIDIA embedded AI platforms, including Jetson Orin or AGX Orin, CUDA, TensorRT, and DeepStream.
You must have experience with agentic AI orchestration, RAG architectures, and sovereign AI data governance.
You must have experience with platform architecture, including microservices, event-driven architecture, and Terraform/Bicep IaC.
You must have experience leading C-suite client engagements, pre-sales, and product roadmap development.
You must have consulting experience at a Tier 1 firm or equivalent.
Experience with Sovereign AI Factory deployments, including on-premises Azure Stack or air-gapped environments (preferred).
Prior experience leading a product practice at a global systems integrator or technology consulting firm (preferred).
Familiarity with industrial AI standards, including ISA-95 or IEC 62443 (preferred).
An advanced degree in Computer Science, Electrical Engineering, or a related field (preferred).
Generative AI
LLMs
RAG
Agentic AI
LangChain
LangGraph
Semantic Kernel
AutoGen
CrewAI
Azure
Azure Databricks
Microsoft Fabric
Azure OpenAI
Azure AI Foundry
Azure Machine Learning
AKS
Delta Lake
Vector Databases
Knowledge Graphs
Azure Synapse Analytics
Azure Data Lake Storage
Cosmos DB
Azure SQL
Azure AI Search
Event Hubs
Service Bus
API Management
Microservices
Data Engineering