Azure AI Tech Lead/Solution Architect

Cognizant; Greater London; Híbrido; GBP 110.000 - 150.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

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

Herramientas

CI/CD tooling

Descripción del empleo

We are seeking an experienced AI Tech Lead to architect and lead the delivery of secure, scalable, cloud-native AI solutions on Microsoft Azure. The role combines enterprise solution architecture, Generative AI, integration architecture, security, DevSecOps governance, and technical leadership across complex programmes.

Key Responsibilities

• Define Azure solution architecture and cloud-native designs aligned with enterprise standards, scalability, resilience, and integration requirements.
• Architect AI solutions using Azure OpenAI, Retrieval-Augmented Generation (RAG), and multi-agent orchestration patterns.
• Establish AI governance, responsible AI controls, observability, and appropriate guardrails for enterprise AI solutions.
• Design API-led, microservices-based, and event-driven integration architectures using appropriate enterprise integration patterns.
• Define secure-by-design architectures incorporating OIDC, SAML, RBAC, Zero Trust, identity, authentication, and authorization controls.
• Provide technical leadership across solution design, engineering, integration, deployment, and operational readiness.
• Drive DevSecOps governance, CI/CD practices, architecture reviews, and engineering quality standards.
• Ensure solutions meet performance, scalability, reliability, security, and maintainability expectations.
• Collaborate with engineering teams, architects, product owners, business stakeholders, and delivery leadership to translate requirements into implementable technical solutions.
• Lead technical decision-making, manage architectural risks and dependencies, and communicate solution options and trade-offs clearly to stakeholders.

Required Skills & Experience

• Strong expertise in Azure Solution Architecture, cloud-native design, and enterprise integration architecture.
• Hands-on knowledge of Azure OpenAI and experience designing Generative AI solutions using RAG architectures.
• Good understanding of multi-agent orchestration, AI governance, responsible AI principles, and enterprise AI security.
• Strong experience with API Management, microservices, event-driven architecture, and common integration patterns.
• Strong knowledge of security architecture, including OIDC, SAML, RBAC, Zero Trust, and Secure by Design principles.
• Experience establishing and governing DevSecOps practices for enterprise-scale solutions.
• Proven ability to design for scalability, resilience, performance, observability, and operational supportability.
• Strong technical leadership, stakeholder management, problem-solving, and communication skills.
• Experience working in Agile delivery environments and collaborating across multidisciplinary engineering