AI Architecture – Enterprise GenAI, LLMs, RAG, Agentic AI, Azure/AWS & MLOps
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Protocol Intelligence
Data-driven signals on your job's competitivenessNiche senior AI-architect role with specialized LLM/MLOps skills reduces competition despite Bengaluru metro.
Highly specialized ML/AI architecture and LLM platform skills limit cross-industry transferability.
Explicit 10+ years requirement and many mandatory LLM, cloud, MLOps, and governance skills.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and implementation of enterprise-scale AI and Generative AI platforms using Azure OpenAI, AWS Bedrock, and LLM orchestration frameworks.
Establish AI governance, platform standards, and oversee delivery of complex AI programs ensuring scalability, security, compliance, and business alignment.
Manage multidisciplinary teams and communicate AI strategy, architectural decisions, and risks to technical and executive stakeholders.
Minimum Requirements
Minimum 10+ years of experience in AI architecture, software engineering, machine learning, data platforms, or related technical fields.
Extensive hands-on expertise with Azure and/or AWS cloud AI services, including Azure OpenAI Services and AWS Bedrock.
Strong technical skills in Generative AI, LLMs, RAG pipelines, Agentic AI frameworks (e.g., LangChain, LangGraph), vector databases, and MLOps tools.
Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, or related discipline; MBA or leadership qualification preferred.
Ideal Candidate Profile
Experienced leader capable of influencing and managing cross-functional teams and large-scale AI delivery programs with measurable outcomes.
Technical strategist proficient in cloud-native AI platform architecture, secure multi-agent systems, and AI governance frameworks.
Demonstrates robust expertise in both AI technology ecosystems and business stakeholder communication for enterprise transformation.