AI Agentic Architect / Lead – Generative AI & Autonomous Systems

About Cognizant (Nasdaq-100: CTSH)

Cognizant engineers modern businesses. As a Nasdaq-100 leader, we help our clients modernize technology, reimagine processes, and transform experiences so they can stay ahead in our fast-changing world. Together, we are improving everyday life. At Cognizant, you will work on the bleeding edge of technology, helping global enterprises transition from simple AI tools to fully autonomous business ecosystems.

The Role: AI Agentic Architect/Lead

We are seeking an AI Agentic Architect to serve as the primary visionary for our autonomous AI systems. This is a high-impact leadership role responsible for the end-to-end design, development, and production deployment of complex Agents.

You will bridge the gap between experimental GenAI and robust, scalable enterprise applications. If you are an expert in multi-agent orchestration, LLMOps, and secure AI architecture, this is the opportunity to define the next era of industrial intelligence.

Key Responsibilities

1. System Design & AI Architecture

• Agentic Frameworks: Lead the selection and implementation of frameworks like LangChain, LlamaIndex, LangGraph, and CrewAI.

• Context Engineering: Design dynamic context modules using sophisticated memory modules, prompt templates, and advanced retrieval strategies.

• Security & Governance: Define and enforce guardrails and context governance across agent interactions to prioritize secure architecture patterns.

2. Full-Stack ML/AI Engineering

• End-to-End Lifecycle: Own the full AI lifecycle, including data sourcing, model development, orchestration, and LLMOps.

• Prototyping to MVP: Rapidly validate technical feasibility through prototypes and scale them into robust enterprise applications that meet core KPIs.

• Optimization: Determine the strategic application of fine-tuning versus prompt engineering to maximize model performance and cost-efficiency.

3. LLMOps & CI/CD Automation

• Monitoring: Establish robust monitoring strategies using cloud-native tools like Azure Monitor and Application Insights.

• Governance: Institute LLMOps practices for tracking model iterations, deployment gates, and active drift detection.

• Pipelines: Design and automate CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins to ensure rapid, reliable deployment.

Qualifications & Technical Expertise

• Experience: Demonstrated expertise in architecting and deploying AI/ML solutions on leading cloud platforms (Azure, AWS, or GCP).

• Programming: Mastery of Python and modern AI frameworks.

• Workflows: Proven hands-on experience designing multi-agent workflows and tool-augmented reasoning systems.

• Leadership: Ability to act as the authority on critical architectural trade-offs and represent the technical interface to stakeholders and product owners.

How to Apply

Ready to engineer the future? Send your resume directly to jwalesh.b@cognizant.com.

To learn more about how we are reimagining business, visit www.cognizant.com or follow us @cognizant.