below marketmost similar roles pay hereabove market
This role pays less than
91%
of similar roles. Most pay
$167,125–$235,750
— the blue band above.
At the midpoint, this role pays about
$141k
versus about
$201k
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.
The Senior Consulting Manager - AI Architecture & Engineering joins the consulting team to translate business priorities into secure, scalable, production-grade AI platforms and customer-facing solutions. You will define target architectures, reference patterns, and engineering standards for enterprise AI, generative AI, retrieval-augmented generation, and agentic applications. Daily responsibilities include leading solutions from discovery through production operations, performing design reviews, and establishing LLMOps practices for model versioning, observability, and cost optimization. You will architect model-agnostic solutions using frontier models, multi-agent workflows, and vector or graph retrieval. Required technical skills include Angular, TypeScript, C#, .NET, PostgreSQL, Redis, and Google Cloud services like Vertex AI and Gemini. You must demonstrate expertise in distributed systems, CI/CD, and establishing responsible-AI controls within complex enterprise environments.
Define and govern target architectures, reference patterns, and engineering standards for enterprise and generative AI products.
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 and develop architects and engineers while managing technical tradeoffs and vendor assessments.
Translate business priorities into secure, scalable, production-grade AI platforms and customer-facing solutions.
Conduct hands-on design reviews, prototyping, troubleshooting, and critical technical decision-making.
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 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 with full-stack and distributed-system engineering using Angular, TypeScript, C#/.NET, APIs, PostgreSQL/AlloyDB, Redis, vector/graph stores, containers, and Google Cloud services.
LLMOps
MLOps
Agentic AI
AWS
Azure
Cloud
Data Science
AI Engineering
FinOps
red-teaming
Model Risk Management
Multi-agent Orchestration
Data Governance
AI Security
Explainability
Bias Testing