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Agentic AI Architect- W2 Candidates Only

Shrive Technologies LLCUnited States🇺🇸United StatesPosted Oct 12, 2026

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

United States

Posted

Yesterday

MLOpsNLPScikit-learnAzureDatabricksDeep LearningGDPRHugging FacePython

Job Description

Job Summary

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

Key Responsibilities

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 Requirements

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:
- ML projects (supervised/unsupervised, forecasting, NLP, deep learning)
- ML modeling tools: Python, PySpark, Azure ML, Databricks, Scikit-learn
- Microsoft Foundry, Microsoft Agentic Framework
- LLMs, embeddings, vector databases, RAG/GraphRAG, prompt optimization, and safety/guardrails
- GenAI tools: MCP Server, Hugging Face Transformers, OpenAI APIs, and diffusion models (for image generation).
- CI/CD, MLOps/LLMOps, SDLC
- Explainable AI (XAI)
Cloud certifications (Microsoft Azure) is a plus

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