Live opening · Posted 7 hours ago

AI Solution Architect

ZIDEA · Pune City, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 7 hours ago
CompanyZIDEA
LocationPune City, Maharashtra, India (On-site)
Work modeNo
SkillsAzure
SourceLinkedin
ListedPosted 7 hours ago

About the role

Description supplied by the original job listing.

Role: AI Solution Architect
Experience: 10+ years in Architecture, with 3+ years in AI/ML/GenAI Solution Architecture
Location: Pune
Role Overview:
We are looking for an experienced AI Solution Architect to design end-to-end AI solutions and reusable architecture patterns. The role involves defining AI models, RAG and agentic systems, enterprise integrations, security, and deployment strategies while ensuring scalability, reliability, and Responsible AI compliance.
Key Responsibilities:
Solution Architecture: Design end-to-end AI solutions and select appropriate models and orchestration approaches.
GenAI & RAG: Define architectures for LLM/SLM, agentic systems, RAG, and GraphRAG.
Data & Integration: Design enterprise knowledge graphs, vector/graph databases, and API/event-driven integrations.
Security & Deployment: Define identity, networking, security, and deployment architectures across cloud and on-premises environments.
Scalability & Governance: Establish NFRs, resiliency, capacity planning, FinOps, and Responsible AI controls.
Architecture Governance: Conduct architecture reviews, document decisions, and guide implementation teams.
Requirements & Qualifications:
10+ years of architecture experience, including 3+ years in AI/ML/GenAI solution architecture.
Strong knowledge of Azure OpenAI, Microsoft Foundry, LLM/SLM patterns, and agentic systems.
Experience with RAG, GraphRAG, knowledge graphs, vector databases, and graph databases.
Understanding of API/event integration, identity, networking, security, and deployment architectures.
Knowledge of resiliency, FinOps, NFRs, and Responsible AI principles.
Strong architectural documentation and stakeholder management skills.
Key Deliverables:
High-Level Design (HLD) and Low-Level Design (LLD)
Architecture decisions, NFRs, and interface designs
Deployment topology, capacity assumptions, and technical handover
Add a clear application call to actionMake the requirements easier to scan
👉 Interested? Share your CV at rudrakshi.jain@zidea.tech

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