Cloud AI Architect Jobs
Cloud AI Architect jobs are open across technology, financial services, healthcare, and defense, from mid-level to principal and staff engineer, with specializations in LLM integration, MLOps platform design, and multi-cloud AI infrastructure. Find a role that fits from the openings below and apply directly.
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INTRODUCTION
Senior Cloud Data & AI Architect
Must Have Technical/Functional Skills
- Architect enterprise data platforms for data lake, Lakehouse, streaming systems.
- Design data integration and data pipeline patterns
- Should be able to evaluate new technologies and run proof of concepts.
- Should be able to set data and AI strategy for data organization.
- Established data Quality, lineage and metadata standards
- Ensured compliance with privacy, security and regulation
- Drives adoption of responsible AI frameworks
- Created architectural guardrails
- Drive consensus on standards (eg data contracts, lineage) across different data organizations
- Reviews design and elevate architectural thinking across teams
- Creates reusable patterns, templates and reference architectures
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Design and implement AI and Gen AI solution for data value chain
- Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI).
- Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning.
- Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
- Experience with A2A orchestration, agent memory strategies, and tool calling.
- Strong grasp of enterprise architecture, data governance, and security protocols.
- Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines.
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.
- Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
- Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
Roles & Responsibilities
- Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
- Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure
- Design and implement AI and Gen AI solution for data value chain
- Design data integration pipelines (batch, real-time, big data) and analytics platforms
- Define and implement data governance, quality, metadata, and lineage frameworks and should be able to leverage GenAI capabilities.
- Act as a trusted advisor to senior business and IT stakeholders
- Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).
- Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
- Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.
- Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.
Generic Managerial Skills, If any
- 15–20 years of experience in data architecture, data engineering, and analytics platforms
- Strong consulting experience in large BFSI transformation programs
- Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)
- Design and implement AI and Gen AI solution for data value chain
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Experience with cloud data services in AWS, Azure, GCP
- Strong background in data integration, reporting, and big data ecosystems
- Experience working in regulated environments with data governance and compliance requirements
- Excellent stakeholder communication and leadership skills
Salary Range
- $150,000-$175,000 a year
Location
Dallas, TX
Job Function
TECHNOLOGY
Role
Technical Architect
Job Id
413283
Desired Skills
Cloud Architecture
Salary Range
$150,000-$175,000 a year
INTRODUCTION
Senior Cloud Data & AI Architect
Must Have Technical/Functional Skills
- Architect enterprise data platforms for data lake, Lakehouse, streaming systems.
- Design data integration and data pipeline patterns
- Should be able to evaluate new technologies and run proof of concepts.
- Should be able to set data and AI strategy for data organization.
- Established data Quality, lineage and metadata standards
- Ensured compliance with privacy, security and regulation
- Drives adoption of responsible AI frameworks
- Created architectural guardrails
- Drive consensus on standards (eg data contracts, lineage) across different data organizations
- Reviews design and elevate architectural thinking across teams
- Creates reusable patterns, templates and reference architectures
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Design and implement AI and Gen AI solution for data value chain
- Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI).
- Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning.
- Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
- Experience with A2A orchestration, agent memory strategies, and tool calling.
- Strong grasp of enterprise architecture, data governance, and security protocols.
- Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines.
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.
- Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
- Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).
Roles & Responsibilities
- Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
- Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure
- Design and implement AI and Gen AI solution for data value chain
- Design data integration pipelines (batch, real-time, big data) and analytics platforms
- Define and implement data governance, quality, metadata, and lineage frameworks and should be able to leverage GenAI capabilities.
- Act as a trusted advisor to senior business and IT stakeholders
- Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).
- Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.
- Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.
- Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.
Generic Managerial Skills, If any
- 15–20 years of experience in data architecture, data engineering, and analytics platforms
- Strong consulting experience in large BFSI transformation programs
- Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)
- Design and implement AI and Gen AI solution for data value chain
- Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation
- Experience with cloud data services in AWS, Azure, GCP
- Strong background in data integration, reporting, and big data ecosystems
- Experience working in regulated environments with data governance and compliance requirements
- Excellent stakeholder communication and leadership skills
Salary Range
- $150,000-$175,000 a year
Location
Dallas, TX
Job Function
TECHNOLOGY
Role
Technical Architect
Job Id
413283
Desired Skills
Cloud Architecture
Salary Range
$150,000-$175,000 a year
See All 368+ Cloud AI Architect Jobs
Jump back to the full list of openings and apply to any cloud AI architect role that fits.
Find Cloud AI Architect JobsCloud AI Architect Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Boston Consulting25
- NVIDIA22
- Tata Consultancy Services (TCS)15
- Bain & Company10
- Datadog9
Top Industries Hiring
- Technology & Software155
- Consulting & Professional Services78
- Electronics & Hardware30
- Insurance21
- Healthcare & Medical Services11
What Employers Look For
The qualifications that appear most often in cloud AI architect jobs.
- Five or more years of hands-on experience designing production cloud infrastructure on AWS, Azure, or Google Cloud
- Demonstrated experience building and deploying machine learning or generative AI workloads at enterprise scale
- Proficiency with MLOps tooling such as Kubeflow, MLflow, Vertex AI Pipelines, or SageMaker Pipelines
- Strong programming skills in Python and familiarity with model serving frameworks like TensorFlow Serving, TorchServe, or Triton
- Experience with containerization and orchestration using Docker and Kubernetes in a cloud-native environment
- Bachelor's degree in computer science, engineering, or a related technical field, or equivalent professional experience
Tips for Your Cloud AI Architect Job Search
Quantify your AI platform impact
Hiring managers for cloud ai architect roles want to see outcomes, not responsibilities. Replace vague resume lines with metrics that show scale: model latency improvements, cost reductions from optimized inference pipelines, or the number of production workloads you migrated to a managed AI service.
Earn a cloud-provider AI certification
AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, and Azure AI Engineer Associate are the three certifications that appear most frequently in cloud ai architect postings. Holding at least one signals hands-on platform fluency and moves your application past automated filters.
Apply early to roles that fit
Migrate Mate lists cloud ai architect openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings by architecture pattern
Search for specific terms like RAG pipeline, vector database, inference optimization, or AI gateway in job descriptions rather than just the title. Cloud ai architect roles vary widely in scope, and matching your application to the architecture pattern a team is building dramatically improves fit.
Prepare a whiteboard architecture walkthrough
Most cloud ai architect interviews include a live design exercise where you architect an end-to-end AI system under constraints. Practice narrating your decisions aloud, covering data ingestion, model serving, observability, and cost guardrails, because interviewers evaluate your reasoning as much as the final design.
Negotiate for infrastructure ownership scope
When evaluating an offer, clarify whether you own the full AI platform stack or operate within a pre-built internal developer platform. Scope of ownership affects your career trajectory and portfolio depth, so confirm it before accepting rather than discovering it on day one.
Cloud AI Architect Jobs: Frequently Asked Questions
Which companies are hiring the most cloud ai architects?
The companies hiring the most cloud ai architects right now include Boston Consulting, NVIDIA, and Tata Consultancy Services (TCS), with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of June 2026. Demand is concentrated at large cloud-native technology firms and enterprises undergoing AI platform modernization.
How many cloud ai architect jobs are remote?
About 39% of cloud ai architect openings are fully remote or hybrid as of June 2026, reflecting the infrastructure-as-code nature of the work. Roles focused on platform engineering, MLOps architecture, and AI governance tend to be the most remote-friendly, while positions requiring close collaboration with on-site data science teams more often require in-office presence.
How do you become a cloud ai architect?
Start by building deep proficiency on at least one major cloud provider, then layer in hands-on machine learning engineering experience through real projects or open-source contributions. Earn a recognized cloud AI certification to validate platform skills. Move into roles that give you ownership of production AI infrastructure, and progressively take on cross-functional design responsibilities that combine data pipelines, model serving, and security governance.
Can you get hired as a cloud ai architect without direct experience?
It's possible to break into cloud ai architect roles by transitioning from a strong cloud engineering or data engineering background. Build a portfolio that includes a deployed end-to-end AI application on a public cloud provider, document your architecture decisions, and target mid-market companies where architects wear broader hats. Staff-augmentation contracts and internal transfers from cloud infrastructure roles are common entry points.
What does the cloud ai architect interview process look like?
The process typically runs three to five rounds and includes a recruiter screen, a technical phone interview covering cloud services and ML fundamentals, a live system design session where you architect an AI platform under constraints, and a final panel with engineering leadership and product stakeholders. Some employers add a take-home design exercise or ask you to walk through a past architecture decision and its trade-offs.
Where can I find and apply to cloud ai architect jobs?
You can find and apply to cloud ai architect jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the listings to find roles that match your skills and experience level, then apply directly to each position that fits.
See All 368+ Cloud AI Architect Jobs
Jump back to the full list of openings and apply to any cloud AI architect role that fits.
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