below marketmost similar roles pay hereabove market
This role pays more than
63%
of similar roles. Most pay
$159,000–$235,750
— the blue band above.
At the midpoint, this role pays about
$208k
versus about
$197k
for comparable roles.
Based on 240 similar postings.
Employer
About AT&T
AT&T is a US-based telecommunications company providing wireless, broadband, and fiber internet service along with phone and connectivity products for consumers and businesses.
AT&T currently has
100 open roles
on FindRole.
Listed pay typically runs
$106,000–$198,358
across 91 roles with salary data.
The Data & AI Solutions Architect joins the CDO Data & AI Architecture organization to provide leadership across enterprise data, analytics, AI/ML, and Generative AI initiatives. This role involves defining target-state architectures, maintaining technology roadmaps, and leading solution architecture reviews to ensure alignment with security and governance policies. You will partner with cross-functional teams to translate business use cases into scalable solutions, driving decisions for data engineering, automation, and digital transformation. Key responsibilities include evaluating platforms like Databricks, Snowflake, and Microsoft Fabric while governing patterns for APIs, event-driven architectures, and microservices. You will utilize cloud platforms including Azure, AWS, and Google Cloud Platform, alongside GenAI tools such as Azure OpenAI, Copilot, RAG, and vector databases to solve complex enterprise data and knowledge management problems.
Define and maintain target-state architectures, technology roadmaps, and architecture principles for data and AI strategies.
Lead solution architecture reviews to ensure alignment with enterprise standards, security requirements, and governance policies.
Translate business capabilities and use cases into scalable, reusable enterprise solutions across various departments.
Drive technology assessments and architecture decisions for platforms supporting AI, GenAI, and digital transformation.
Establish and govern architecture patterns for data platforms, APIs, event-driven architectures, and cloud-native solutions.
Lead platform and vendor evaluations, proof-of-concepts, and technology selection based on business value and scalability.
Define architecture guardrails and governance processes for responsible AI, data privacy, and risk management.
Author architecture standards, solution patterns, and executive-level presentations for senior leadership and governance forums.
What we're looking for
Experience with cloud platforms including Azure, AWS, and Google Cloud Platform.
Experience with API management, event-driven architectures, enterprise integration patterns, and microservices.
Experience with GenAI platforms such as Azure OpenAI, Copilot ecosystem, Agent frameworks, RAG, vector databases, and knowledge platforms.
10+ years of experience in Enterprise Architecture, Solution Architecture, Data Architecture, Cloud Architecture, or Software Engineering leadership roles (preferred).
Deep understanding of enterprise data ecosystems, AI/ML platforms, Generative AI, Agentic AI, knowledge management, and modern cloud architectures (preferred).
Experience evaluating and governing enterprise platforms such as Databricks, Snowflake, Palantir, Microsoft Fabric, and cloud-native services (preferred).
Proven ability to lead cross-functional architecture initiatives and support enterprise technology modernization and AI adoption strategies (preferred).
Solution Architecture
Data Architecture
Data Modeling
TOGAF
Machine Learning
ETL Architecture
Cloud-native Data Services
Data Warehousing
Data Lakes
Streaming Architectures
Metadata Management
Data Governance
Software Architecture
Platform Architecture
Integration Patterns
non functional requirements
AI/ML Platforms
Generative AI
LLM APIs
Vector Databases
Retrieval-Augmented Generation
LLMOps
AWS Bedrock
Azure AI Services
Google Vertex AI
Prompt Engineering
Data Architecture
Data Modernization
Agent Orchestration
Cloud Engineering
Data Science
Service Design
Generative AI
LLMs
RAG
AWS
Azure
Google Cloud Platform
Vector Databases
Distributed Systems
Microservices
API Architecture
CI/CD
DevSecOps
Platform Engineering
Model Serving
Prompt Orchestration
Agentic AI
IAM
Observability
Generative AI
LLMs
RAG
AWS
Azure
Google Cloud Platform
Vector Databases
Microservices
Distributed Systems
API Architecture
CI/CD
DevSecOps
Platform Engineering
Model Serving
Prompt Orchestration
Agentic AI
IAM
Observability