Senior Cloud Data & AI Architect

Position Overview

We are seeking a highly experienced Senior Cloud Data & AI Architect to lead the design and modernization of enterprise-scale data and AI platforms. The successful candidate will have deep expertise across cloud data architecture, data engineering, AI/GenAI, data governance, and enterprise architecture.

This role will focus on developing scalable data platforms, defining enterprise data and AI strategies, establishing architectural standards, and delivering innovative AI-powered solutions across complex transformation programs.

The ideal candidate will bring strong consulting experience, exceptional stakeholder management skills, and hands-on expertise across modern cloud data and AI technologies.

Key Responsibilities

Lead enterprise data platform modernization and migration initiatives from on-premises environments to cloud platforms.

Architect enterprise-scale Data Lake, Lakehouse, streaming, and analytics platforms.

Design scalable data integration and pipeline architectures supporting batch, real-time, and big data workloads.

Architect and implement cloud data solutions using Snowflake and Databricks across AWS and Azure environments.

Define and execute enterprise data and AI strategies aligned with business objectives.

Design and implement AI and Generative AI solutions across the data value chain.

Architect Agentic AI ecosystems using LLMs, vector databases, orchestration frameworks, and enterprise data platforms.

Design and implement RAG (Retrieval-Augmented Generation) solutions incorporating memory, context management, retrieval, and tool usage.

Define and implement Model Context Protocol (MCP) architectures to connect reasoning, retrieval, and action capabilities.

Design Agent-to-Agent (A2A) communication and orchestration patterns for collaborative multi-agent workflows.

Establish data quality, metadata, lineage, governance, privacy, security, and compliance frameworks.

Define architectural guardrails, standards, reusable patterns, templates, and reference architectures.

Drive adoption of responsible AI frameworks and ensure AI solutions meet enterprise security, privacy, and regulatory requirements.

Establish and promote standards including data contracts, lineage, metadata, and governance frameworks across data organizations.

Evaluate emerging technologies and lead technical proofs of concept (PoCs) to determine their suitability for enterprise adoption.

Review solution designs and elevate architectural practices across engineering, data, and AI teams.

Promote best practices around Data Products, Data Mesh, and Medallion Architecture.

Act as a trusted technical advisor to senior business and IT stakeholders.

Facilitate architectural discussions and drive consensus across multiple teams and business functions.

Provide technical leadership and mentorship to data engineering, AI, and architecture teams.

Required Technical SkillsData & Cloud Architecture

15+ years of experience across data architecture, data engineering, analytics, and enterprise technology.

Strong experience designing enterprise Data Lake, Lakehouse, streaming, and analytics architectures.

Hands-on expertise with Snowflake and Databricks, including Lakehouse architecture.

Strong experience with cloud platforms including AWS, Azure, and/or GCP.

Deep understanding of Data Products, Data Mesh, and Medallion Architecture.

Strong knowledge of data integration, ETL/ELT, real-time streaming, big data, and analytics ecosystems.

Experience designing scalable and highly available enterprise data platforms.

AI & Generative AI

Strong experience designing and implementing AI and Generative AI solutions within enterprise data environments.

Deep understanding of LLMs, prompt engineering, agentic AI, and AI orchestration frameworks.

Hands-on experience with frameworks such as LangChain, AutoGen, and CrewAI.

Strong understanding of MCP (Model Context Protocol), ReAct, Tree of Thought, and autonomous/agent-based AI patterns.

Experience developing RAG pipelines with memory, context management, retrieval, and tool calling.

Experience with Agent-to-Agent (A2A) orchestration and collaborative multi-agent architectures.

Understanding of agent memory strategies, tool calling, reasoning workflows, and context management.

Hands-on development experience with Python.

Experience with LLM platforms and APIs such as OpenAI and Anthropic Claude.

Experience with vector databases such as FAISS, Pinecone, or Weaviate.

Strong understanding of AI security, responsible AI, governance, and enterprise adoption considerations.

Data Governance & Security

Strong understanding of enterprise data governance and architecture principles.

Experience establishing data quality, metadata, lineage, and data governance standards.

Strong knowledge of privacy, security, regulatory, and compliance requirements.

Experience implementing governance frameworks within highly regulated environments.

Ability to establish architectural guardrails and enterprise technology standards.

Consulting & Leadership Skills

15-20 years of overall experience in data architecture, data engineering, analytics, or related technology disciplines.

Strong consulting experience delivering large-scale financial services, banking, insurance, or other regulated-industry transformation programs.

Proven ability to operate as a senior technical advisor to business and IT leadership.

Excellent communication, presentation, influencing, and stakeholder management skills.

Ability to work across multiple technical and business teams and drive consensus on enterprise standards.

Strong architectural leadership with the ability to challenge existing approaches and elevate technical thinking.

Experience creating reusable architectural patterns, templates, frameworks, and reference architectures.

Strong problem-solving and strategic thinking skills.

Comfortable working in complex, enterprise-scale transformation environments.

Preferred Qualifications

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

Cloud certifications such as AWS, Azure, or Google Cloud certifications.

Databricks or Snowflake certifications are highly desirable.

Experience with enterprise-scale MLOps and AI/ML platforms.

Experience leading cloud migration and modernization programs.

Experience working with regulated data environments and enterprise security frameworks.

What You Will Bring

The successful candidate will combine deep data architecture expertise with modern cloud and AI capabilities. You should be comfortable moving between strategic architecture, hands-on technical design, emerging AI technologies, and senior stakeholder engagement.

You will play a key role in shaping the organization’s future cloud data and AI architecture, establishing scalable standards and enabling teams to deliver secure, governed, and innovative data and AI solutions.