Quest Global - Technical Architect - Generative AI

Note : If shortlisted, you will be invited for initial rounds on 20th June 2026, Saturday in Bangalore Key Responsibilities : - Architect and deliver enterprise-scale AI/GenAI solutions using LLMs, RAG, and Agentic AI. - Define AI architecture standards, governance frameworks, and best practices. - Design scalable and secure AI platforms on AWS, Azure, or hybrid environments. - Lead AI platform modernization and enterprise AI adoption initiatives. - Establish AI observability, monitoring, evaluation, and operational practices. - Collaborate with business and technology stakeholders to translate business needs into AI solutions. - Mentor engineering teams on AI architecture, frameworks, and implementation best practices. - Evaluate emerging AI technologies and recommend strategic investments and roadmaps. - Act as a trusted advisor to leadership on AI strategy, governance, and enterprise transformation. Work Experience : Mandatory Skills : - AI / GenAI Architecture : LLMs, RAG, Agentic AI, AI Automation, Prompt Engineering, Enterprise AI Solutions - AI Platforms & Frameworks : LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen or equivalent - AI Engineering : Production-grade AI services, AI Observability, Evaluation, Monitoring, Guardrails, Model Context Protocol (MCP), A2A Protocol - Programming : Python/Java/C#/Node.js - Cloud & Containerization : AWS, Azure, Docker, Kubernetes, ECS, EKS, AKS - Architecture & Design : Microservices, API-first, Event-driven Architecture, Distributed Systems, REST, gRPC - Integration & Messaging : Kafka, RabbitMQ, Redis, Service Bus, Pub/Sub Patterns - Data & AI Operations : MLOps, AIOps, ETL Pipelines, ML Lifecycle Management, Vector Databases and Semantic Search - Security & Governance : AI Governance, Responsible AI, IAM, API Security, Cloud Governance - Leadership : Stakeholder Management, Architecture Governance, Technical Leadership Nice to Have : - Multi-Agent Orchestration Platforms - ML/Data Science experience - ITSM / AIOps Platforms - AI Platform Modernization Programs - AWS/Azure AI Certifications Qualifications : - Bachelors degree in computer science, Engineering, or related field. - Up to 12 years of technology experience. - 5+ years in Solution/Enterprise Architecture. - 2 years architecting and delivering AI/GenAI solutions in production. - Experience building enterprise-scale AI platforms and services. - Strong communication, stakeholder management, and leadership skills. - Cloud and AI certifications preferred. Note : If shortlisted, you will be invited for initial rounds on 20th June 2026, Saturday in Bangalore Key Responsibilities : - Architect and deliver enterprise-scale AI/GenAI solutions using LLMs, RAG, and Agentic AI. - Define AI architecture standards, governance frameworks, and best practices. - Design scalable and secure AI platforms on AWS, Azure, or hybrid environments. - Lead AI platform modernization and enterprise AI adoption initiatives. - Establish AI observability, monitoring, evaluation, and operational practices. - Collaborate with business and technology stakeholders to translate business needs into AI solutions. - Mentor engineering teams on AI architecture, frameworks, and implementation best practices. - Evaluate emerging AI technologies and recommend strategic investments and roadmaps. - Act as a trusted advisor to leadership on AI strategy, governance, and enterprise transformation. Work Experience : Mandatory Skills : - AI / GenAI Architecture : LLMs, RAG, Agentic AI, AI Automation, Prompt Engineering, Enterprise AI Solutions - AI Platforms & Frameworks : LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen or equivalent - AI Engineering : Production-grade AI services, AI Observability, Evaluation, Monitoring, Guardrails, Model Context Protocol (MCP), A2A Protocol - Programming : Python/Java/C#/Node.js - Cloud & Containerization : AWS, Azure, Docker, Kubernetes, ECS, EKS, AKS - Architecture & Design : Microservices, API-first, Event-driven Architecture, Distributed Systems, REST, gRPC - Integration & Messaging : Kafka, RabbitMQ, Redis, Service Bus, Pub/Sub Patterns - Data & AI Operations : MLOps, AIOps, ETL Pipelines, ML Lifecycle Management, Vector Databases and Semantic Search - Security & Governance : AI Governance, Responsible AI, IAM, API Security, Cloud Governance - Leadership : Stakeholder Management, Architecture Governance, Technical Leadership Nice to Have : - Multi-Agent Orchestration Platforms - ML/Data Science experience - ITSM / AIOps Platforms - AI Platform Modernization Programs - AWS/Azure AI Certifications Qualifications : - Bachelors degree in computer science, Engineering, or related field. - Up to 12 years of technology experience. - 5+ years in Solution/Enterprise Architecture. - 2 years architecting and delivering AI/GenAI solutions in production. - Experience building enterprise-scale AI platfo