Job Summary

Role Overview We are looking for an AI Architect with 15+ years of enterprise technology experience to define and drive the organizations AI architecture strategy across Generative AI, Machine Learning, and Agentic AI systems. The ideal candidate will design scalable AI platforms, establish governance standards, and lead enterprise-wide AI transformation initiatives.

Responsibilities

- Define enterprise-wide AI architecture frameworks, standards, and long-term technology roadmaps.

- Design scalable AI platforms supporting Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and predictive Machine Learning solutions.

- Architect multi-agent systems, AI orchestration frameworks, vector database ecosystems, and enterprise AI data pipelines.

- Design and implement multi-cloud AI architectures across Azure, AWS, and Google Cloud Platform (GCP).

- Establish AI governance standards covering MLOps, LLMOps, Responsible AI, security, compliance, and model lifecycle management.

- Drive cost optimization strategies for AI infrastructure, LLM usage, and enterprise AI platform scalability.

- Evaluate emerging AI technologies, GenAI models, agent frameworks, and recommend build, buy, or partner strategies.

- Collaborate with CXOs, business stakeholders, and engineering teams to align AI initiatives with business goals and ROI.

- Support enterprise solution architecture, large transformation programs, and strategic AI proposals.

Required Skills & Qualifications

- 15+ years of experience in enterprise software architecture, distributed systems, and large-scale platform design.

- Strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI agent architectures.

- Extensive experience designing enterprise Machine Learning systems including NLP,



forecasting, recommendation, and optimization solutions.

- Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar multi-agent platforms.

- Deep understanding of MLOps, LLMOps, AI model lifecycle management, API-first architectures, and enterprise AI governance.

- Strong knowledge of distributed systems, microservices architecture, event-driven systems, and cloud-native application design.

- Experience with modern data platforms including Databricks, Apache Spark, Lakehouse architecture, and vector database technologies.

- Expertise in designing AI solutions across Azure, AWS, and Google Cloud Platform (GCP).

- Excellent leadership, stakeholder management, technology evaluation, and enterprise architecture decision-making skills.

Preferred Qualifications

- Experience as an Enterprise Architect, Principal Architect, AI Architect, or Chief Architect leading enterprise AI initiatives.

- Industry certifications in Cloud Architecture (Azure, AWS, or GCP) and AI/ML technologies are highly preferred.

- Experience defining enterprise AI governance frameworks, Responsible AI policies, and security best practices.

- Exposure to Agentic AI frameworks, autonomous AI systems, and enterprise AI orchestration platforms.

- Experience working with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or similar technologies.

- Robust understanding of enterprise integration patterns, hybrid cloud architectures, and AI platform modernization.

- Experience supporting executive leadership, digital transformation programs, and enterprise AI strategy development.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Architect (Bengaluru)
🏢 Devlats
📍 Bengaluru