Role & responsibilities

- Lead the architecture and design of enterprise AI and Generative AI solutions.

- Design scalable solutions using Microsoft Foundry / Azure AI Foundry, Azure OpenAI, and Azure AI services.

- Architect LLM, RAG, AI Agent, embeddings, vector search, and enterprise knowledge retrieval solutions.

- Translate customer business requirements into practical and production-ready AI architectures.

- Conduct customer workshops, technical discovery sessions, and architecture discussions.

- Review solution architectures across AI, applications, data, integration, infrastructure, and security.

- Define reference architectures, technical standards, reusable patterns, and implementation approaches.

- Evaluate models and architecture options based on accuracy, scalability, latency, security, reliability, and cost.

- Design secure integrations between AI applications, APIs, enterprise systems, and data platforms.

- Ensure solutions address performance, resilience, observability, monitoring, privacy, and access-control requirements.

- Review technical designs and implementation approaches created by engineering teams.

- Provide technical direction to AI Engineers, Data Engineers, Cloud Architects, and development teams.

- Resolve complex architecture decisions, technical risks, and implementation blockers.

- Support pre-sales and solutioning activities for AI and Generative AI opportunities.

- Contribute to solution scope, technical approach, assumptions, dependencies, and effort estimates.

- Guide AI proof-of-concepts and prototypes toward secure and scalable production deployments.

- Develop reusable AI accelerators, reference implementations,



and architecture assets.

- Present architecture recommendations, trade-offs, and technical decisions to senior customer stakeholders.

Preferred candidate profile The ideal candidate should have:

- 5+ years of relevant experience across AI/ML, software engineering, cloud architecture, solution architecture, or data engineering.

- Strong recent hands-on experience designing and delivering Generative AI solutions.

- Practical experience with Microsoft Foundry / Azure AI Foundry and Azure OpenAI.

- Strong understanding of Large Language Model (LLM) application architecture.

- Hands-on experience designing Retrieval-Augmented Generation (RAG) solutions.

- Experience with AI Agents, Agentic AI, tool/function calling, and agent-based workflows.

- Experience with embeddings, vector search, vector databases, and enterprise knowledge retrieval.

- Robust experience with cloud-native application architecture on Microsoft Azure.

- Experience designing APIs, integrations, microservices, and distributed applications.

- Knowledge of enterprise security including identity, networking, authentication, authorization, data privacy, and access control.

- Ability to design AI solutions for production with consideration for scalability, availability, reliability, monitoring, latency, security, and cost.

- Ability to review technical architecture and implementation approaches created by engineering teams.

- Strong customer-facing communication, consulting, presentation, and stakeholder-management skills.

- Ability to communicate complex technical concepts to both engineers and senior business/technology stakeholders.

📌 Artificial Intelligence Architect (Bengaluru)
🏢 Neostats Analytics Solutions
📍 Bengaluru