AI Architect / Generative AI Architect

About the Role

We are looking for an experienced AI Architect to lead the design, development, and deployment of enterprise-scale Artificial Intelligence solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Agentic AI, RAG architectures, Machine Learning, Cloud Platforms, and Enterprise Solution Architecture.

You will work closely with business stakeholders, data scientists, engineering teams, and product leadership to build scalable AI platforms and transform business processes through AI-driven innovation.

Key Responsibilities

• Design and architect end-to-end AI/GenAI solutions aligned with business objectives.
• Define enterprise AI strategy, architecture standards, and best practices.
• Build and implement Generative AI applications leveraging LLMs, RAG, Agents, and multi-agent frameworks.
• Design scalable AI platforms using Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent cloud services.
• Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
• Evaluate and recommend AI frameworks, models, tools, and infrastructure.
• Define data, model, and deployment architectures ensuring scalability, security, and governance.
• Lead AI solution design reviews and provide technical leadership during implementation.
• Ensure AI solutions comply with security, privacy, and responsible AI principles.
• Drive MLOps/LLMOps practices for model deployment, monitoring, observability, and lifecycle management.
• Mentor engineering and data science teams on AI architecture and best practice

Required Skills & Qualifications

AI & Machine Learning

• Strong experience in Machine Learning and Deep Learning concepts.
• Hands-on expertise with Large Language Models (LLMs).
• Experience with Generative AI solution development.
• Knowledge of Retrieval-Augmented Generation (RAG).
• Experience building Agentic AI and autonomous AI workflows.
• Prompt Engineering and AI model optimization.

Technical Skills

• Strong programming expertise in Python.
• Experience with PyTorch, TensorFlow, Scikit-Learn.
• Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen.
• API integration and microservices architecture experience.

Cloud & Infrastructure

• Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
• Knowledge of Docker and Kubernetes.
• Experience designing cloud-native AI solutions.

Data & Platforms

• Experience with SQL and NoSQL databases.
• Experience with Vector Databases such as Pinecone, Weaviate, ChromaDB, or Milvus.
• Strong understanding of data architecture and data engineering principles.

Architecture & Governance

• Enterprise Architecture and Solution Design expertise.
• AI Governance, Responsible AI, Model Monitoring, and Compliance frameworks.
• Strong understanding of scalability, reliability, and security architecture.