below marketmost similar roles pay hereabove market
This role pays less than
80%
of similar roles. Most pay
$184,900–$238,500
— the blue band above.
At the midpoint, this role pays about
$173k
versus about
$212k
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.
Consulting Principal - AI Architecture and Engineering Lead joins the consulting team as an Associate Director to translate business priorities into secure, scalable, production-grade AI platforms. 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 with prototyping and critical technical decisions. Key responsibilities include establishing LLMOps practices for model versioning, CI/CD, and observability. 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, LlamaIndex, and LangGraph to build model-agnostic solutions featuring multi-agent workflows and vector or graph retrieval.
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, stateful agents, and multi-agent workflows.
Establish LLMOps practices including prompt versioning, automated evaluation, CI/CD, observability, and cost optimization.
Mentor and develop architects and engineers while partnering with cross-functional leaders to prioritize use cases.
Perform hands-on design reviews, prototyping, troubleshooting, and critical technical decision-making.
Assess emerging AI technologies and vendors to manage technical and business tradeoffs.
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
Generative AI
Agentic AI
AWS
Google Cloud Platform
Java
Spring Boot
Microservices
LangChain
LangGraph
CrewAI
AutoGen
Retrieval-Augmented Generation
Vector Databases
Pinecone
Weaviate
Chroma
FAISS
Large Language Models
OpenAI
Anthropic Claude
Google Gemini
APIs
Event-driven Architecture
Distributed Systems
GitHub Copilot
Microsoft Copilot