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Role Overview
As a Solution Architect, you will be responsible for designing and governing end-to-end data, analytics, and GenAI solutions on Microsoft Azure. You will translate business and functional requirements into scalable, secure, and cost-optimized architectures, enabling advanced analytics, AI, and GenAI-powered applications. You will work closely with business stakeholders, product teams, data engineers, and AI/ML teams to ensure solutions are technically sound, future-ready, and aligned with enterprise standards.
Key Responsibilities – Solution Architect
Design end-to-end enterprise data and AI architectures on Microsoft Azure
Define solution architecture for data ingestion, processing, analytics, and GenAI use cases
Architect lakehouse and data platform solutions using ADLS Gen2, Databricks, Synapse
Design scalable ETL/ELT and streaming architectures using Azure Data Factory, Event Hubs, Kafka, Spark
Define GenAI and LLM architectures, including RAG-based solutions
Select and integrate vector databases (Azure AI Search, Pinecone, Milvus, FAISS)
Architect secure integration with GenAI frameworks and APIs (Azure OpenAI, LangChain, Hugging Face)
Establish data modeling, data quality, and governance standards
Define cloud security architecture using Azure AD, RBAC, Key Vault, Private Endpoints, and Purview
Design high-availability, scalable, and cost-optimized cloud solutions
Define CI/CD and DevOps architecture for data and AI pipelines
Provide architecture blueprints, reference designs, and best practices
Guide teams on technology selection and design trade-offs
Review and approve solution designs and technical implementations
Partner with business, product, and engineering teams to translate requirements into architecture
Support pre-sales, estimations, and technical proposals
Ensure solutions align with enterprise architecture, security, and compliance standards
Drive architecture governance and design reviews
Required Skills
Languages: Python, SQL, PySpark
Cloud Platform: Microsoft Azure, AWS
Data & Analytics: Azure Data Factory, Databricks, Synapse Analytics, ADLS Gen2
Streaming & GenAI: Azure Event Hubs, Kafka, Azure OpenAI, Azure AI Search, Vector DBs (Pinecone, Milvus, FAISS)
DevOps & Platform: Docker, AKS (Kubernetes), Azure DevOps / GitHub Actions, Terraform / ARM / Bicep
Preferred Skills
Experience with GenAI / LLM architectures, including RAG, embeddings, and vector databases.
Exposure to MLOps / LLMOps, data governance, security, and compliance practices.
Strong skills in performance tuning, cost optimization, and technical stakeholder communication.
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