Senior AI Architect

About Atos Group

Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. €10 billion, operating in 61 countries under two brands — Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Job Title: Senior AI Architect – Any of the Cloud (Azure | AWS | GCP)

Role Summary

We are seeking a highly experienced Senior AI Architect to lead enterprise AI solutioning across Microsoft Azure or Amazon Web Services (AWS), or  Google Cloud Platform (GCP). This role requires deep expertise in Generative AI, Large Language Models (LLMs), AI services, and cloud-native AI architecture.

The ideal candidate will drive AI strategy, pre-sales engagements, RFP/RFI solutioning, architecture design, PoC development, and customer workshops across multi-cloud environments. The role involves close collaboration with the AI Practice Lead and cross-functional cloud, data, and domain teams to deliver scalable, secure, and production-grade AI solutions.

Key Responsibilities:-

AI Strategy & Architecture

• Lead the design and implementation of enterprise AI solutions across

 Microsoft Azure / Amazon Web Services /Google Cloud Platform.

• Architect Generative AI, LLM, and Machine Learning solutions using native AI services across all three clouds.


• Define reference architectures, security frameworks, and scalability models for AI workloads.

Generative AI & LLM Solutions

• Design and implement solutions using:




• Azure OpenAI Service


• Azure Cognitive Services


• Microsoft 365 Copilot


• Amazon Bedrock


• Amazon SageMaker


• Google Vertex AI




• Implement LLM-based use cases: document intelligence, chatbots, enterprise search, code assistants, summarization, recommendation systems.


• Apply prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation), embeddings, and vector databases.

Pre-Sales & Customer Engagement

• Participate in customer presentations, workshops, and executive briefings.


• Lead technical discussions and solution positioning during pre-sales cycles.


• Drive RFP/RFI responses including:




• Architecture diagrams


• Effort estimations


• Technical solution write-ups


• Compliance and security considerations




• Build professional, client-ready PowerPoint presentations and demo environments.

PoC & Innovation

• Design and develop Proofs of Concept (PoCs) demonstrating multi-cloud AI capabilities.


• Build reusable accelerators and solution templates.


• Stay updated on Azure, AWS, and GCP AI roadmaps and introduce innovation within the practice.

Collaboration & Leadership

• Work closely with cloud architects, data engineers, DevOps teams, and domain SMEs.


• Mentor junior team members and promote knowledge sharing.


• Establish best practices for AI governance, responsible AI, and cost optimization.

Required Technical Skills:-

Azure AI Expertise

• Strong experience with:




• Azure OpenAI Service (GPT models, embeddings)


• Azure Cognitive Services (Form Recognizer, Vision, Translator)


• Azure Machine Learning


• Azure Functions


• Azure Logic Apps




• Deep knowledge of Microsoft 365 Copilot extensibility (Graph APIs, plugins, connectors).

AWS AI Expertise

• Experience with:




• Amazon Bedrock


• Amazon SageMaker


• Amazon Comprehend


• Amazon Lex




• Designing scalable ML pipelines and MLOps on AWS.

GCP AI Expertise

• Hands-on experience with:




• Google Vertex AI


• Dialogflow


• Document AI




• Implementing ML pipelines and AI workloads in GCP .

Core AI & Engineering Skills

• Strong Python programming skills.


• RESTful API design and JSON integrations.


• LLM fine-tuning, prompt engineering, embeddings, semantic search.


• Experience with vector databases (Pinecone, FAISS, Azure AI Search, etc.).


• Knowledge of LangChain, Semantic Kernel, Prompt Flow.


• CI/CD for ML, MLOps, containerization (Docker, Kubernetes).


• Security, identity, and governance in multi-cloud AI architectures.

Soft Skills

• Excellent communication and presentation skills.


• Strong stakeholder management and executive engagement capability.


• Ability to lead solutioning discussions independently.


• Strategic thinking with innovation mindset.


• Collaborative and mentoring-oriented approach.

Role Impact

This role will drive enterprise AI transformation across Azure, AWS, and GCP, enabling customers to adopt secure, scalable, and production-ready AI solutions leveraging best-of-breed cloud AI services.