below marketmost similar roles pay hereabove market
This role pays less than
80%
of similar roles. Most pay
$179,500–$251,000
— the blue band above.
At the midpoint, this role pays about
$173k
versus about
$215k
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
408 open roles
on FindRole.
Listed pay typically runs
$100,000–$135,000
across 266 roles with salary data.
The Consulting Principal - AI Architecture joins the consulting team to translate business priorities into secure, scalable, production-grade AI platforms and customer-facing solutions. This role involves defining target architectures, reference patterns, and engineering standards for enterprise AI, generative AI, retrieval-augmented generation, and agentic applications. You will lead solutions from discovery through production operations, remaining hands-on in prototyping and critical technical decisions. Key responsibilities include establishing LLMOps practices for prompt versioning, automated evaluation, and cost optimization. Required technical skills include expertise in LLM application engineering, distributed systems, and cloud architecture using Angular, TypeScript, C#, .NET, PostgreSQL, Redis, and Google Cloud services. You will also utilize frameworks like LangChain and LlamaIndex to build model-agnostic solutions featuring multi-agent workflows, vector retrieval, and secure enterprise integrations.
Define and govern target architectures, reference patterns, and engineering standards for enterprise and generative AI.
Lead solutions from initial discovery and architecture through implementation, deployment, and production operations.
Architect model-agnostic AI solutions using frontier models, multi-agent workflows, and vector or graph retrieval.
Establish LLMOps practices including prompt versioning, automated evaluation, CI/CD, observability, and cost optimization.
Mentor architects and engineers while partnering with cross-functional leaders to prioritize use cases and assess vendors.
Perform hands-on design reviews, prototyping, troubleshooting, and critical technical decision-making.
Implement responsible-AI controls, security integrations, and reliability standards for production-grade AI platforms.
What we're looking for
12+ years of software, platform, data, or cloud engineering experience.
5+ years of experience in architecture or technical leadership with demonstrated delivery of enterprise-scale production AI systems.
Hands-on expertise in LLM application engineering, agents, retrieval-augmented generation, evaluation, guardrails, distributed systems, cloud architecture, and multiple model providers.
Experience establishing secure AI platform and LLMOps practices including CI/CD, observability, automated evaluation, incident response, privacy, security, governance, resilience, and cost optimization.
Experience guiding full-stack and distributed-system engineering using Angular, TypeScript, C# and .NET, APIs, PostgreSQL or AlloyDB, Redis, vector or graph stores, containers, and Google Cloud services.
AI
LLM
Agentic Workflows
Vector Search
AI Orchestration
Distributed Systems
APIs
Cloud-Native
Data Platforms
AI Governance
Observability
Security
Privacy
Compliance