BlueCloud Services, Inc. - AI/ML Architect
Requirements
• 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. • 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. • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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.
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