GenAI & Agentic AI Architect

Cognizant

Amsterdam, Netherlands

2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

dejobs.org

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Program Optimization Python (Programming Language) Machine Learning Performance Tuning Tensorflow Search Technologies Pytorch Large Language Models

+13 more

Multi-Agent Systems Prompt Engineering Spring-boot Generative AI Build Management Scikit Learn Kubernetes Performance Monitor Machine Learning Operations Virtual Agents Serverless Computing Docker Microservices

Job description

We are seeking a highly experienced GenAI & Agentic AI Architect with strong hands-on expertise to lead the design, development, and implementation of advanced AI solutions for our clients. This role requires a seasoned technical leader with over 8 years of architecture experience and deep knowledge of Azure and/or AWS cloud ecosystems, combined with strong capabilities in containerization, orchestration, observability, and modern AI frameworks., * Architect and develop scalable, high-performance Generative AI solutions on Azure and/or AWS platforms

Design, build, and manage containerized AI applications using Docker and orchestrate deployments via Kubernetes
Establish and maintain observability frameworks for LLMs, including performance monitoring, system health, and usage analytics
Develop and implement machine learning models using Python or R, leveraging frameworks such as TensorFlow, PyTorch, or scikit-learn
Build and deploy AI/ML solutions using cloud-native services such as AWS SageMaker, Azure AI, or Google Vertex AI
Design and implement multi-agent systems and Retrieval-Augmented Generation (RAG) architectures
Define and enforce standards for prompt engineering, vector search, and model orchestration
Build and manage enterprise-grade MLOps pipelines covering model training, fine-tuning, evaluation, deployment, and monitoring
Collaborate with cross-functional teams to integrate AI capabilities into enterprise products and platforms
Lead system optimization, performance tuning, and troubleshooting of AI-driven applications
Establish best practices for secure, scalable, and maintainable AI architectures
Mentor and guide AI engineering teams on emerging technologies and implementation best practices
Stay current with advancements in Generative AI, Agentic AI, and cloud technologies

Requirements

Minimum 8+ years of experience in a technical architecture role
Proven expertise in Azure and/or AWS cloud architectures
Strong hands-on experience with Docker and Kubernetes
Proficiency in Python or R with experience in TensorFlow, PyTorch, or scikit-learn
Deep knowledge of MLOps practices and model deployment on AWS SageMaker, Azure AI, or Google Vertex AI
Experience with multi-agent orchestration and RAG architectures
Solid understanding of prompt engineering, vector search, and LLM observability frameworks
Experience with Spring Boot and microservices architecture
Strong understanding of enterprise AI security, scalability, and governance principles