Cloud Data AI Architect

Role Summary

We are looking for an experienced Cloud Data & AI Architect to design and implement scalable cloud-based data and AI solutions. The ideal candidate should have strong experience in cloud architecture, data engineering, data platforms, Generative AI, machine learning, and enterprise architecture.

Key Responsibilities

• Design end-to-end Cloud Data & AI architecture for enterprise applications and platforms.

• Build scalable data solutions using AWS, Azure, or Google Cloud Platform (GCP).

• Architect modern Data Lakes, Data Warehouses, Lakehouse, and Data Mesh solutions.

• Design data ingestion, transformation, integration, and analytics pipelines.

• Work with technologies such as Databricks, Snowflake, Spark, Kafka, and cloud-native data services.

• Design and implement AI/ML and Generative AI solutions using LLMs.

• Develop architecture for RAG, vector databases, AI agents, and enterprise GenAI applications.

• Define data architecture, governance, security, quality, and integration standards.

• Work with business and technical stakeholders to understand requirements and convert them into architecture solutions.

• Lead technical discussions, architecture reviews, solution design, and proof-of-concept activities.

• Evaluate new Data & AI technologies and recommend appropriate solutions.

• Provide technical leadership to data engineers, AI/ML engineers, developers, and other architecture teams.

• Ensure solutions meet requirements for scalability, performance, security, reliability, and cost optimization.

Required Skills

• Strong experience as a Data Architect, Cloud Architect, Data & AI Architect, or Solution Architect.

• Strong hands-on knowledge of at least one cloud platform: AWS / Azure / GCP.

• Experience with Databricks and/or Snowflake.

• Strong understanding of Data Lake, Data Warehouse, Lakehouse, ETL/ELT, and data pipelines.

• Experience with Spark, Kafka, Python, SQL, APIs, and distributed data processing.

• Knowledge of Machine Learning, Generative AI, LLMs, RAG, embeddings, and vector databases.

• Understanding of data governance, security, metadata management, and data quality.

• Experience designing enterprise-scale cloud and data solutions.

• Strong communication and client-facing skills.

Preferred Skills

• Cloud certifications in AWS, Azure, or GCP.

• Databricks or Snowflake certification.

• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI models, or similar AI platforms.

• Experience with MLOps / LLMOps and AI model deployment.

• Experience working in large enterprise environments and leading architecture discussions.

Experience

Typically 10+ years of overall IT experience, including significant experience in cloud, data architecture, data engineering, and AI/ML solutions.

Education

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Technology, or a related field.