Solution Architect

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.