AI Delivery Lead - Generative AI & Azure

About the role

Accenture is looking for an experienced Generative AI / Azure AI Engineering Lead with 11+ years of IT experience in AI engineering, machine learning and cloud-based AI solution delivery. The role covers designing, developing and deploying enterprise-grade AI solutions on Microsoft Azure, including Azure OpenAI, Azure AI Foundry, Azure AI Search, RAG, Agentic AI, Python, LangChain and Azure Functions. It also involves leading technical teams and delivering client-facing AI solutions.

Key responsibilities

• Lead the architecture, design, development and implementation of enterprise Generative AI solutions on Microsoft Azure.
• Build end-to-end RAG applications and integrate Azure OpenAI models for summarization, knowledge retrieval, Q&A, content generation and workflow automation.
• Design Agentic AI and multi-agent architectures, and develop Python orchestration pipelines for agents, business rules, scoring and structured JSON outputs.
• Implement document intelligence workflows (OCR, text extraction, chunking, embeddings, vector indexing) and configure Azure AI Search indexes.
• Design secure, scalable cloud-native solutions with Managed Identity, Azure AD, Key Vault, RBAC, logging and monitoring.
• Translate business requirements into solution designs, define architecture, integration patterns and deployment roadmaps, and ensure reliable, traceable AI responses.
• Lead technical teams and prepare architecture diagrams, technical documentation, PoCs and client presentations.

Required profile

• 11+ years of overall IT experience in application development, AI engineering, machine learning, cloud solutions or data-driven delivery.
• Hands-on experience designing and deploying Generative AI solutions on Azure, including Azure OpenAI, Azure AI Search, RAG, embeddings and vector databases.
• Experience building multi-agent AI solutions and integrating AI with enterprise apps, databases, APIs, SharePoint and cloud storage.
• Experience leading technical teams and working with business stakeholders, architects, product owners and client teams.
• Ability to prepare architecture diagrams, design documents, implementation plans and client-facing materials.

Required skills

• Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure Blob Storage, Azure Key Vault, Azure Monitor, Application Insights
• RAG pipelines, Agentic AI, LangChain, LlamaIndex, Promptflow, FastAPI, Python, SQL, PostgreSQL, Supabase, Git, CI/CD, Docker, Azure Container Apps
• Machine learning and NLP concepts (BERT, Word2Vec, TF-IDF, LSTM, RNN, XGBoost, MLOps)