AI Architect

Cognizant; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Cognizant is seeking a seasoned AI Architect to lead design and deployment of scalable Agentic AI platforms. This client-facing role requires translating complex AI concepts into enterprise value on Google Cloud Platform (GCP).

You will collaborate with Enterprise Architecture, AI CoE, and security teams to deliver secure, production-grade AI solutions and multi-agent workflows.

Qualifications

• Hands-on experience architecting and deploying Agentic/Generative AI in production.
• Deep expertise with Google Cloud Platform, Vertex AI, and IAM/Security.
• Strong understanding of enterprise IT governance and compliance.

Responsibilities

• Design end-to-end architecture for production-grade Agentic AI systems.
• Serve as onsite technical liaison with client EA teams and AI CoE.
• Collaborate with partners to align integration patterns and security.
• Architect GCP infrastructure using Vertex AI, Cloud Run, and secure pipelines.
• Guide multi-agent workflows and RAG pipelines into production.

Skills

Production Agentic AI Experience

Deep GCP Cloud Expertise

Enterprise Architecture Acumen

Communication & Executive Presence

Core Engineering Background

Job description

Location: Nashville, Tennessee (Client Office) or Remote with travel on need basis

Role Overview:

We are seeking a highly experienced, client-facing AI Architect to lead the technical design and enterprise-wide deployment of scalable Agentic AI platforms. In this high-visibility role, you will act as the primary technical bridge between our engineering pods and the client’s internal technology teams. You will be responsible for defining the architectural blueprint, ensuring enterprise-grade security and reliability, and guiding complex multi-agent workflows into production on Google Cloud Platform (GCP).

Key Responsibilities:

• Technical Leadership & Blueprinting: Design and own the end-to-end architecture for production-grade Agentic AI systems, transitioning prototypes into secure, highly available enterprise applications.
• Stakeholder & Partner Alignment: Serve as the primary onsite technical liaison interfacing directly with the client’s Enterprise Architecture (EA) teams, AI Center of Excellence (AI CoE), Cloud Engineering, and Information Security boards.
• Cross-Partner Collaboration: Collaborate with external technology partners and marketplace vendors to establish best practices, integrate third-party APIs, and align on shared integration patterns.
• GCP Infrastructure Design: Architect robust AI infrastructure leveraging the GCP ecosystem, including Vertex AI, Gemini models, Cloud Run, Cloud Storage, and secure deployment pipelines.
• Agentic Workflow Design: Guide offshore engineering pods in the development of complex multi-agent orchestration (e.g., LangGraph, LangChain), RAG pipelines, and automated evaluation frameworks.

Required Qualifications:

• Production Agentic AI Experience: Proven, hands-on track record of successfully architecting, building, and deploying Agentic AI / Generative AI systems into live enterprise production environments (not just prototypes or hackathons).
• Deep GCP Cloud Expertise: Extensive experience with Google Cloud Platform, specifically Vertex AI, serverless deployments (Cloud Run/Functions), and IAM/Security configurations.
• Enterprise Architecture Acumen: Strong understanding of enterprise IT governance, network security, and compliance guardrails required to deploy AI in highly regulated environments.
• Communication & Executive Presence: Exceptional ability to translate complex AI engineering concepts into strategic business value for executive stakeholders, while negotiating technical trade-offs with client EAs and security officers.
• Core Engineering Background: Solid foundation in modern software engineering practices, CI/CD for machine learning (MLOps/LLMOps), API design, and observability (e.g., LangSmith).