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.
We are currently hiring for an
Azure Generative AI Architect Solution Development Role to design and deliver enterprise-grade GenAI platforms and applications.
The role focuses on building
scalable AI solutions using Azure OpenAI, Azure AI Studio, and the broader Azure AI ecosystem while aligning with enterprise architecture, governance, and security standards.
Experience Required -
10+ years of overall IT experience with
5+ years in AI/ML, Data Science, or AI solution architecture.
Location - Pune , Mumbai, Bangalore and Chennai (Hybrid )
Role Overview -
The
Azure GenAI Architect will lead the design and implementation of
enterprise-scale Generative AI solutions using
Azure OpenAI, AI Studio, and modern LLM frameworks.
This role requires a combination of
solution architecture expertise, hands-on development experience, and strategic consulting capability to translate business problems into
secure, scalable AI-powered applications.
The architect will work closely with
data teams, application engineers, DevOps teams, and business stakeholders to drive AI adoption across the organization.
Key Responsibilities -
GenAI Architecture & Solution Design
- Design scalable Generative AI architectures using Azure OpenAI Service (GPT-4, GPT-4o, embeddings).
- Build enterprise Retrieval Augmented Generation (RAG) architectures using Azure AI Search and vector databases.
- Architect AI-powered applications such as knowledge assistants, enterprise search, document intelligence, copilots, and conversational AI systems.
- Define GenAI reference architectures, reusable components, and best practices.
AI Platform Engineering -
- Implement AI workflows using Azure AI Studio, Azure Machine Learning, and Azure Cognitive Services.
- Design LLMOps pipelines for model lifecycle management, monitoring, evaluation, and continuous improvement.
- Build scalable APIs and services using Azure Functions, API Management, AKS, and container-based architectures.
- Develop secure and scalable prompt orchestration frameworks.
Enterprise AI Integration -
- Integrate GenAI capabilities with enterprise applications and data platforms including Data Lake, Databricks, and enterprise APIs.
- Work with data engineering teams to design pipelines for document ingestion, embeddings generation, and knowledge indexing.
- Enable multi-model architectures supporting Azure OpenAI and external model providers.
AI Governance & Responsible AI -
- Implement Responsible AI frameworks, governance policies, and risk mitigation strategies.
- Ensure compliance with enterprise security standards, data privacy, and regulatory requirements.
- Establish best practices for model evaluation, hallucination mitigation, and prompt safety.
Client & Solution Leadership -
- Lead technical discussions with clients, stakeholders, and executive leadership.
- Contribute to solution proposals, architecture presentations, and RFP/RFI responses.
- Mentor engineering teams and guide GenAI adoption strategies.
Required Skills & Competencies -
Generative AI Technologies
- Hands-on experience with Azure OpenAI Service (GPT models, embeddings, fine-tuning concepts).
- Experience building RAG pipelines and LLM-powered applications.
- Strong knowledge of prompt engineering, model evaluation, and LLM optimization.
LLM Frameworks & Development
- Strong proficiency in Python.
- Experience with LangChain, Semantic Kernel, or LlamaIndex.
- Experience building REST APIs, microservices, and scalable backend services.
- Knowledge of vector databases, embeddings, and semantic search.
Cloud & DevOps
- Experience implementing MLOps / LLMOps pipelines.
- Familiarity with CI/CD pipelines, containerization, and Kubernetes-based deployments.
- Strong understanding of Azure security (Managed Identity, Key Vault, RBAC, encryption).
Preferred Qualifications -
- Microsoft Certified Azure AI Engineer Associate
- Microsoft Certified Azure Solutions Architect Expert
- Experience designing enterprise AI platforms and AI Centers of Excellence (CoE).
- Experience working with Copilot Studio or building enterprise copilots.
- Exposure to multi-cloud GenAI environments (Azure, AWS, GCP).
Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.
Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.
Choose your future. Choose Atos. 
