ROLE OVERVIEW :

We are looking for a Technical Architect with deep expertise in Azure and AI to design and deliver enterprise-grade agentic applications. The ideal candidate can independently lead architecture decisions, work across data, AI, and cloud layers, and guide engineering teams from design through production.

KEY RESPONSIBILITIES :

- Architect end-to-end AI solutions on Azure from data ingestion and semantic modelling to agent orchestration and deployment.

- Design agentic application patterns: multi-agent systems, tool use, memory, and reasoning pipelines using LangChain, Agnos ,Lang graph or Similar.

- Own knowledge graph and semantic layer design for structured data-driven AI use cases.

- Define LLM integration patterns - Azure OpenAI, prompt engineering, RAG pipelines, NL2SQL, and output guardrails.

- Lead the design of Azure-native infrastructure: Container Apps, Azure Functions, Azure AI Search, Cosmos DB, and Key Vault.

- Collaborate with client stakeholders to translate business problems into technical architectures.

- Provide technical governance and hands-on guidance to engineering teams throughout delivery.

- Drive POC and prototype development - quick, structured, and outcome-focused.

REQUIREMENTS





- 8-10 years in AI / data / cloud architecture with hands-on delivery experience

- Strong Azure stack expertise: Azure OpenAI, Azure AI Search, Cosmos DB/Neo4j , Container Apps, and Azure DevOps.

- Proven experience designing agentic AI applications - not just RAG chatbots.

- Solid Python skills

- Familiarity with knowledge graphs, ontology design, or semantic data modelling is a strong advantage.

- Databricks knowledge is a plus.

- Strong communicator able to present architecture to both technical and business stakeholders.

- Bachelor's / Master's in Computer Science, AI, or related discipline.

DESIRED TECHNICAL SKILLS

- AI &
- Agents: Azure OpenAI, LangChain, LlamaIndex, Lang graph , Agnos , Semantic Kernel, multi-agent orchestration

- Knowledge &

- Data: Cosmos DB, Neo4j, ontology/semantic modelling, NL2SQL, Microsoft Purview

- Vector &

- Search: Azure AI Search, embedding models, RAG, semantic similarity

- Cloud &

- Infra: Azure Container Apps, Azure Functions, Key Vault, Azure DevOps, Terraform

- Data Platforms: Azure SQL, Azure Synapse, Azure Data Factory -Databricks a plus

- Guardrails: Output sanitization, PII filtering, confidence scoring, lineage logging

📌 Azure AI Architect (Bengaluru)
🏢 Mastech
📍 Bengaluru