AI Architect

Key Skills & Expertise:
✅ Generative AI, RAG (Retrieval-Augmented Generation) & LLM Optimization
✅ Strong Python programming with TensorFlow, PyTorch & Pandas
✅ Experience with Azure AI Foundry and AI Search
✅ MLOps & Cloud Infrastructure (Docker, Kubernetes, MLflow)
✅ Data Engineering & Databases (PostgreSQL, SQL Server)
✅ Workflow Orchestration using Apache Airflow, Azure Data Factory (ADF) & Logic Apps
✅ Solution Architecture for scalable, secure, and production-ready AI systems

Job Purpose (both Onsite / Offshore) 
We are seeking a highly experienced AI Architect with 10+ years in data and AI engineering, and deep 
hands-on expertise in Agentic AI systems, multi-LLM architecture, GenAI, Retrieval-Augmented 
Generation (RAG), and AI platform governance. 
This role will lead the design and implementation of enterprise-grade AI solutions built on the 
Microsoft Azure ecosystem, combining architectural leadership with active engineering involvement. 
The ideal candidate must be able to operate at both: 
• Strategic architecture level 
• Hands-on implementation level 
 
 
Job Description / Duties and Responsibilities  
• Define AI/ML solution architecture and oversee implementation across projects using Microsoft 
Azure services. 
• Lead and mentor a team of AI engineers and data scientists. 
• Own the end-to-end lifecycle of AI models – from ideation and data acquisition to deployment 
and monitoring.
• Partner with business stakeholders to translate requirements into AI solutions. 
• Evaluate emerging tools, frameworks, and platforms for AI/ML development. 
 
• Drive standardization, code quality, and best practices across the AI engineering team. 
 
• Ensure ethical, explainable, and compliant AI practices. 
 
• Define LLM routing, fallback, and evaluation strategies 
 
• Design and implement autonomous AI agents using Azure OpenAI Service and Azure AI Studio 
 
• Build multi-agent orchestration systems 
 
• Implement memory management (short-term & vector-based long-term memory) 
 
• Design agent safety guardrails and oversight mechanisms 
 
• Architect end-to-end RAG pipelines 
 
• Implement hybrid search (semantic + keyword) 
 
• Optimize retrieval grounding and hallucination mitigation 
 
• Tune prompts and evaluate model performance 
 
 
Job Specification / Skills and Competencies 
• Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. 
• 10+ years of experience in AI/ML development with demonstrated leadership in delivering 
production-grade AI solutions. 
• Deep expertise in machine learning, deep learning, NLP, or computer vision. 
• Experience with model architecture design, feature stores, model monitoring. 
• Strong experience with MLOps, DevOps for ML, and deployment tools (Docker, Kubernetes, MLflow, Airflow). 
• Solid understanding of cloud AI/ML offerings (Azure ML, SageMaker, Vertex AI). 
• Proven ability to lead technical teams and manage delivery timelines.