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.