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AI Architect

RapidIT, IncUnited States🇺🇸United StatesPosted Sep 28, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
23 hours ago
MLOpsNLPScikit-learnAzureDatabricksDeep LearningGDPRHugging FacePython

Job Description

Job Title/Role: AI Architect

Job Location/Client Location: Redmond, WA (Preferred)

Remote ok (Yes / No) Yes

JD Responsibilities

• 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

 

Skill & Experience

• 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

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