below marketmost similar roles pay hereabove market
This role pays less than
55%
of similar roles. Most pay
$160,770–$225,000
— the blue band above.
At the midpoint, this role pays about
$190k
versus about
$193k
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 senior Forward Deployed AI Engineer joins the Artificial Intelligence and Analytics practice to architect, build, and operationalize enterprise-scale AI systems for complex client transformation programs. You will design AI-native architectures, build production-grade Generative AI, RAG, and agentic AI solutions, and develop guardrail specifications for safety and regulatory compliance. Key responsibilities include creating human-agent operating models, context pipelines, and knowledge orchestration frameworks while leading technical discovery sessions and executive-level solution discussions. Required skills include hands-on experience with Java, .NET, and Python, alongside deep knowledge of multi-agent architectures, MLOps, AIOps, and cloud-native AI architecture. You will solve technical problems regarding bias detection, explainability, and model risk within regulated industries like financial services, healthcare, and government by establishing robust responsible AI controls and production standards.
Design and deliver AI-native enterprise architectures across applications, data platforms, and cloud environments.
Build and deploy production-grade Generative AI, RAG, and agentic AI solutions.
Define human-agent operating models, escalation paths, and human-in-the-loop controls for enterprise workflows.
Architect context pipelines, knowledge orchestration frameworks, and multi-agent systems.
Develop guardrail specifications for agent boundaries, data handling, safety, and exception management.
Establish responsible AI controls for bias detection, explainability, and regulatory compliance.
Lead client architecture workshops, technical discovery sessions, and executive-level solution discussions.
Evaluate frontier models through structured benchmarking, red teaming, and safety testing.
What we're looking for
12–20 years of experience in enterprise technology, including leadership in AI architecture, solution architecture, or digital transformation.
Proven experience designing and delivering enterprise-scale Generative AI, RAG, LLM, and agentic AI solutions in production environments.
Strong hands-on software engineering experience with Java, .NET, Python, or comparable enterprise application technologies.
Deep understanding of multi-agent architectures, context engineering, knowledge orchestration, tool use, memory, planning, and human-agent collaboration patterns.
Experience defining responsible AI frameworks, agent guardrails, evaluation standards, audit controls, and regulated AI decisioning models.
Strong knowledge of cloud-native AI architecture, APIs, microservices, data platforms, DevSecOps, MLOps, AIOps, and enterprise integration patterns.
Experience evaluating frontier models, conducting AI red-team exercises, and defining AI quality, security, performance, and safety criteria.
Experience delivering AI solutions in regulated industries such as financial services, healthcare, life sciences, insurance, or government (preferred).
Agentic AI
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Enterprise Architecture
Multi-Agent Systems
Responsible AI
AI Governance
Cloud-native AI Architectures
MLOps
Azure
AWS
GCP
AI Security
Human-in-the-Loop AI Systems