Senor AI Data Architect

🚀 We’re Hiring | Senior AI Data Architect

📍 Location: Hyderabad, India | 🏢 Work Mode: On-site

💼 Experience: 15–20 Years | Employment: Full-Time**

About Magnarus

Magnarus is an outsourced product development and technology solutions company specializing in building secure, reliable, and scalable digital products. We work with businesses across industries to deliver technology solutions that enable growth, digital transformation, and operational efficiency.

We are looking for an experienced Senior AI Data Architect to define and drive modern data and AI architecture across product development and client engagements.

Role Overview

The Senior AI Data Architect will be responsible for designing scalable, secure, and high-performance data architectures that support AI, Machine Learning, Generative AI, analytics, and enterprise applications .

The role requires a strong combination of data architecture, cloud, AI/ML, data engineering, solution architecture, and technical leadership , along with the ability to work closely with business, product, engineering, and client stakeholders.

Key Responsibilities

• Define and lead enterprise data and AI architecture for products, platforms, and client solutions.

• Design scalable architectures for data lakes, data warehouses, lakehouses, data platforms, and AI/ML workloads .

• Design data architectures supporting Generative AI, LLMs, RAG, NLP, vector search, and AI-driven applications .

• Define data ingestion, integration, transformation, processing, storage, and serving architectures for structured and unstructured data.

• Design and evaluate real-time, batch, streaming, and event-driven data architectures based on business and technical requirements.

• Establish architecture standards for data quality, governance, metadata, lineage, security, privacy, and access control .

• Work closely with Data Scientists, AI/ML Engineers, Software Engineers, DevOps, Product Managers, and Business teams to translate requirements into scalable technical solutions.

• Evaluate and select appropriate cloud, data, AI, database, and integration technologies based on scalability, performance, security, cost, and business requirements.

• Define architecture patterns for AI/ML model development, deployment, monitoring, evaluation, and lifecycle management .

• Design solutions for integrating enterprise data with LLMs, vector databases, knowledge bases, and AI agents .

• Provide technical leadership and architectural guidance across multiple projects and client engagements.

• Review existing architectures, identify gaps, and define modernization and migration strategies .

• Establish reusable architecture patterns, reference architectures, technical standards, and best practices.

• Mentor architects, engineers, and data professionals and contribute to building the organization’s Data & AI architecture capabilities .

Key Skills

**Data Architecture AI Architecture Cloud Architecture Data Engineering Data Lakes Data Warehouses Lakehouse Big Data SQL Python ETL/ELT Data Modeling Data Governance Machine Learning Generative AI LLMs RAG Vector Databases API Architecture Real-Time/Streaming Data Data Security**

Cloud & Technology Experience

Experience with one or more major cloud and data platforms such as:

**AWS Microsoft Azure Google Cloud Databricks Snowflake BigQuery Azure Data Lake AWS Data Lake Azure AI AWS AI/ML Google Vertex AI**

Experience with technologies such as Kafka, Spark, Airflow, dbt, Kubernetes, Docker, PostgreSQL, NoSQL databases, and vector databases is desirable.

Required Qualifications

• 15–20 years of experience in Data Architecture, Data Engineering, Solution Architecture, AI/ML Architecture, or related technology domains.

• Strong experience designing and implementing enterprise-scale data architectures and platforms .

• Proven experience with cloud-based data architecture and modern data platforms .

• Strong understanding of data modeling, data integration, ETL/ELT, data pipelines, data governance, metadata, lineage, and data security .

• Strong understanding of AI/ML architecture and data requirements for machine learning systems .

• Practical experience designing architectures for Generative AI, LLM, RAG, NLP, vector search, or AI-enabled applications .

• Strong understanding …