Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
AI/ML Architect - Talent Pipeline
- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Remote — work setting source
Work setup in the employer’s posting: remote
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingBlueCloud is seeking an experienced AI/ML Architect to lead the architecture and delivery of enterprise-scale AI, machine learning, and Generative AI solutions.
This is a hands-on architecture role requiring recent experience designing, developing, integrating, and deploying production-grade AI solutions.
Architect and deliver end-to-end AI/ML and Generative AI solutions to production
Design RAG systems, vector search, embedding pipelines and AI agents
Lead hands-on implementation using Snowflake Cortex and Snowpark ML
Integrate AI solutions with AWS, Azure or GCP and enterprise systems
Define reusable AI reference architectures and governance frameworks
From the employer’s posting
BlueCloud is seeking an experienced AI/ML Architect to lead the architecture and delivery of enterprise-scale AI, machine learning, and Generative AI solutions.
This is a hands-on architecture role requiring recent experience designing, developing, integrating, and deploying production-grade AI solutions. You will work directly with enterprise clients to translate complex business needs into scalable, secure, and governed architectures across Snowflake, cloud platforms, data ecosystems, and enterprise applications.
Architect and deliver end-to-end AI/ML and Generative AI solutions from discovery through production deployment.
Design production-grade RAG systems, vector search solutions, embedding pipelines, AI agents, copilots, and multi-agent workflows.
Lead hands-on implementation using Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and related Snowflake AI capabilities.
Integrate AI solutions with AWS, Azure, or GCP, as well as enterprise applications, APIs, ETL/ELT platforms, streaming systems, and third-party AI services.
Define reusable AI reference architectures, accelerators, technical standards, and governance frameworks.
What you’ll bring
All qualificationsCore experience
- 10+ years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.
- Proven experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.
- Strong understanding of machine learning, deep learning, NLP, MLOps, and LLMOps.
- Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps.
- Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.
- Strong understanding of AI security, governance, compliance, observability, and model monitoring.
Preferred experience
- Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Azure ML, or Vertex AI.
- Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or MCP.
- Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or pgvector.
- Experience integrating AI solutions with platforms such as Salesforce, ServiceNow, SAP, Workday, or Microsoft applications.
Qualification wording
10+ years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.
Proven experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.
Strong understanding of machine learning, deep learning, NLP, MLOps, and LLMOps.
Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps.
Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.
Strong understanding of AI security, governance, compliance, observability, and model monitoring.
Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Azure ML, or Vertex AI.
Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or MCP.
Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or pgvector.
Experience integrating AI solutions with platforms such as Salesforce, ServiceNow, SAP, Workday, or Microsoft applications.
Posting record
Report an errorOpen 3 monthsWe first saw this posting 95 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Aug 1, 202695 days ago
- Recorded sightings
- 32
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Jul 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 95
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,301 similar postings that came down. Coming down is not always a hire.
Blue Trust is hiring
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- AWS
- Azure
- GCP
- Kafka
- SageMaker
- Snowflake
Where the posting names them
- Design scalable ML and LLM pipelines supporting training, inference, evaluation, monitoring, and governance. - Integrate AI solutions with AWS, Azure, or GCP, as well as enterprise applications, APIs, ETL/ELT platforms, streaming systems, and third-party AI services. - Define reusable AI reference architectures, accelerators, technical standards, and governance frameworks.
- Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps. - Strong architecture experience across Snowflake and at least one major cloud platform, preferably AWS or Azure. - Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.
- Experience integrating AI solutions with platforms such as Salesforce, ServiceNow, SAP, Workday, or Microsoft applications. - Snowflake, AWS, Azure, or AI/ML certifications. - Consulting experience within regulated industries such as financial services, healthcare, or manufacturing.
Preferred Qualifications - Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Azure ML, or Vertex AI. - Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or MCP.
- Strong architecture experience across Snowflake and at least one major cloud platform, preferably AWS or Azure. - Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures. - Strong understanding of AI security, governance, compliance, observability, and model monitoring.
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth.
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth. We don't just strategize — we execute.
BlueCloud is seeking an experienced AI/ML Architect to lead the architecture and delivery of enterprise-scale AI, machine learning, and Generative AI solutions. This is a hands-on architecture role requiring recent experience designing, developing, integrating, and deploying production-grade AI solutions. You will work directly with enterprise clients to translate complex business needs into scalable, secure, and governed architectures across Snowflake, cloud platforms, data ecosystems, and enterprise applications. Key Responsibilities
- Design production-grade RAG systems, vector search solutions, embedding pipelines, AI agents, copilots, and multi-agent workflows. - Lead hands-on implementation using Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and related Snowflake AI capabilities. - Design scalable ML and LLM pipelines supporting training, inference, evaluation, monitoring, and governance.
- Strong understanding of machine learning, deep learning, NLP, MLOps, and LLMOps. - Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps. - Strong architecture experience across Snowflake and at least one major cloud platform, preferably AWS or Azure.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches.
With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth.
We don't just strategize — we execute.
About the Role
BlueCloud is seeking an experienced AI/ML Architect to lead the architecture and delivery of enterprise-scale AI, machine learning, and Generative AI solutions.
This is a hands-on architecture role requiring recent experience designing, developing, integrating, and deploying production-grade AI solutions. You will work directly with enterprise clients to translate complex business needs into scalable, secure, and governed architectures across Snowflake, cloud platforms, data ecosystems, and enterprise applications.
Key Responsibilities
-
Architect and deliver end-to-end AI/ML and Generative AI solutions from discovery through production deployment.
-
Design production-grade RAG systems, vector search solutions, embedding pipelines, AI agents, copilots, and multi-agent workflows.
-
Lead hands-on implementation using Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and related Snowflake AI capabilities.
-
Design scalable ML and LLM pipelines supporting training, inference, evaluation, monitoring, and governance.
-
Integrate AI solutions with AWS, Azure, or GCP, as well as enterprise applications, APIs, ETL/ELT platforms, streaming systems, and third-party AI services.
-
Define reusable AI reference architectures, accelerators, technical standards, and governance frameworks.
-
Provide technical leadership through architecture reviews, code reviews, design sessions, and production-readiness assessments.
-
Lead client discovery workshops, solution design, effort estimation, technical presentations, proof-of-concepts, and pre-sales activities.
-
Collaborate with data engineers, ML engineers, application teams, architects, and business stakeholders throughout delivery.
Required Qualifications
-
10+ years of experience in solution architecture, AI/ML architecture, enterprise architecture, or technical delivery.
-
Strong recent hands-on experience building and supporting production AI/ML and Generative AI solutions.
-
Proven experience with LLMs, RAG, vector databases, embedding pipelines, agentic AI, prompt engineering, and AI evaluation.
-
Strong understanding of machine learning, deep learning, NLP, MLOps, and LLMOps.
-
Hands-on experience with Snowflake Cortex, Cortex Analyst, Cortex Search, Cortex Agents, Snowpark ML, and Snowflake Native Apps.
-
Strong architecture experience across Snowflake and at least one major cloud platform, preferably AWS or Azure.
-
Experience integrating AI platforms with APIs, microservices, SaaS applications, enterprise systems, Kafka, and event-driven architectures.
-
Strong understanding of AI security, governance, compliance, observability, and model monitoring.
-
Excellent client-facing communication, technical leadership, and stakeholder-management skills.
-
Ability to balance strategic architecture ownership with hands-on technical execution.
Preferred Qualifications
-
Experience with Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Azure ML, or Vertex AI.
-
Familiarity with LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or MCP.
-
Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, or pgvector.
-
Experience integrating AI solutions with platforms such as Salesforce, ServiceNow, SAP, Workday, or Microsoft applications.
-
Snowflake, AWS, Azure, or AI/ML certifications.
-
Consulting experience within regulated industries such as financial services, healthcare, or manufacturing.
We are looking for someone who is experienced in building lasting relationships and is passionate about making meaningful contributions to our team. Don't be mistaken, this is a challenging career path but also highly rewarding. Are you up for the challenge? If so, stop reading and start applying.
Employment type
Bench hiring
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