Azure AI Tech Lead: Scalable, Secure GenAI Architect

Cognizant; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Job summary

Cognizant in London seeks an experienced AI Tech Lead to architect and lead the delivery of secure, scalable, cloud-native AI solutions on Microsoft Azure. You will drive enterprise solution architecture, Generative AI, and governance across complex programmes.

Lead cross-functional teams, define secure-by-design architectures, and ensure involving stakeholders receive high-quality, reliable AI capabilities.

Qualifications

• Proven experience in Azure-based AI architecture.
• Designs Generative AI solutions with scalable patterns.
• Knowledge of governance and secure-by-design practices.
• Experience with API-led integration and microservices.

Responsibilities

• Define Azure solution architecture aligned with enterprise standards.
• Architect AI solutions using Azure OpenAI and RAG.
• Establish AI governance and guardrails.
• Design API-led, microservices-based integration architectures.
• Define secure-by-design architectures with OIDC/SAML/RBAC.
• Provide technical leadership across delivery and operations.
• Drive DevSecOps governance and CI/CD practices.
• Ensure performance, scalability, security and maintainability.
• Collaborate with engineering teams and stakeholders.
• Lead technical decision-making and manage dependencies.

Skills

Azure Solution Architecture

Cloud-native design

Enterprise integration

Azure OpenAI

RAG architectures

Multi-agent orchestration

AI governance

Secure by design

API Management

Microservices

Event-driven architecture

DevSecOps leadership

Stakeholder management

Effective communication

Tools

CI/CD tooling

Job description

Cognizant in London seeks an experienced AI Tech Lead to architect and lead the delivery of secure, scalable, cloud-native AI solutions on Microsoft Azure. You will drive enterprise solution architecture, Generative AI, and governance across complex programmes.

Lead cross-functional teams, define secure-by-design architectures, and ensure involving stakeholders receive high-quality, reliable AI capabilities.