AI/ML Architect - Talent Pipeline
BlueCloud · United States · Yesterday
RemoteRemoteArt & CreativeFull-time
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.
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.