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AI Architect

Laiba Technologies LLCRedmond, WA🇺🇸United StatesPosted Oct 19, 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Redmond, WA, United States
Posted
Yesterday
MLOpsNLPScikit-learnAzureDatabricksDeep LearningGDPRHugging FacePython

Job Description

Position: AI Architect
Location: Redmond, WA (Onsite)

• 15+ years in Data/AI/ML Engineering 
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Azure App Insights 

Hands-on with: 
o ML projects (supervised/unsupervised, forecasting, NLP, deep learning) 
o ML modeling tools: Python, PySpark, Azure ML, Databricks, Scikit-learn 
o Microsoft Foundry, Microsoft Agentic Framework 
o LLMs, embeddings, vector databases, RAG/GraphRAG, prompt optimization, and safety/guardrails 
o GenAI tools: MCP Server, Hugging Face Transformers, OpenAI APIs, and diffusion models (for image generation). 
o CI/CD, MLOps/LLMOps, SDLC 
o Explainable AI (XAI) 
• Cloud certifications (Microsoft Azure) is a plus
• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks 
• Build AI solutions using frameworks such as Microsoft Agent Framework – Autogen, Semantic Kernel, Copilot Studio 
• Well-versed with the Microsoft Agentic Framework (MAF) 
• Build RAG pipelines, vector DB integrations & autonomous workflow orchestration 
• Design and lead ML project lifecycles — data prep, modeling, training, evaluation, deployment & MLOps 
• Govern full SDLC for Data, ML, and GenAI platforms 
• Ensure strong security, compliance, governance (GDPR, CCPA, PII) 
• Produce robust architecture blueprints, ML design docs, and runbooks 
• Engage with customer IT and business leaders to understand pain points, priorities, success measures, and risks. 
• Design secure, scalable data and AI solutions to deliver measurable business value. 
• Lead architecture design sessions, develop data/AI and analytics roadmaps to drive PoCs and MVPs. 
• Accelerate adoption and ensure long-term technical viability. 
• Deliver Production-ready GenAI/Agentic applications. 
• Fine-tuned models and reproducible experiments. 
• Provide Clear documentation, test coverage, and deployment pipelines. 
• Regular updates on project status and deliverables to stakeholders. 
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops 

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